Job Title: Principal Software Engineering - Build System Modernization Company: General Motors (GM) Job Category: Machine Learning Roles & Responsibilities: Job Description As part of the application process, Artificial Intelligence will be used in the hiring process for this role Hybrid: This role is categorized as hybrid. This means the successful candidate is expected to report to Markham or Oshawa office three times per week, at minimum. The Role: General Motors is seeking a software engineering leader to modernize and scale the build systems that support software\-defined vehicles. This role will help lead the transition from a legacy Make\-based system to Bazel, Google’s open\-source build tool, improving speed, reliability, and robustness across the engineering organization. The successful candidate will drive this capability at scale, influence technical direction across teams, and help establish lofty platform capability goals. * Lead software engineering productivity and effectiveness by identifying opportunities, shaping strategies, improving processes, guiding change, and connecting initiatives to deliver greater value through innovation, learning, and simplification. * Lead high\-impact efforts hands\-on, solve complex and unusual problems, and communicate effectively as a coach and mentor while balancing technical command with empathy. * Modernize a large embedded\-software build and test system by transitioning legacy Make\- or shell\-based workflows to Bazel and establishing scalable, reproducible, secure, and developer\-friendly infrastructure across repositories, toolchains, CI/CD, testing, and release processes. * Assess current build, test, dependency, toolchain, and hardware workflows to define a phased Bazel migration strategy and rollout model. * Design and implement reusable Bazel rules, macros, toolchains, platforms, configuration patterns, and repository standards, while migrating embedded applications, libraries, generated code, firmware, cross\-compilation flows, and platform variants with validated build parity and reproducibility. * Integrate Bazel with enterprise CI/CD, testing, release, artifact, deployment, observability, security, and infrastructure workflows, and optimize the platform through caching, parallelism, reliability practices, documentation, training, legacy Make retirement, and continuous improvement. * Measure success through target repositories migrated with validated build and test parity; faster clean and incremental builds, CI queues, and developer feedback; increased reproducibility, approved hermetic\-toolchain adoption, cache effectiveness, and CI capacity; and lower build, pipeline, and flaky\-test rates. * Improve diagnosis and recovery time while ensuring complete artifact provenance, test evidence, and security\-policy compliance for releases, strong developer adoption, reduced support burden, and measurable productivity improvement. * Hold a bachelor’s degree in software engineering or have equivalent experience, along with 15 years of software development experience. * Bring a deep understanding of real\-time software architecture and experience shipping high\-quality, safety\-critical products in automotive, embedded, safety\-related, calibration, or systems\-engineering environments. * Demonstrate exceptional problem\-solving and analytical abilities, keen attention to detail, and the ability to manage multiple projects and priorities in fast\-paced, action\-oriented decision\-making environments. * Bring strong expertise building and maintaining production software systems, proficiency in Python and at least one additional engineering\-tooling language, and experience with AI\-assisted developer productivity, coding agents, code intelligence, knowledge retrieval, or workflow orchestration. Evaluate AI\-enabled engineering workflows using measurable quality, adoption, and productivity outcomes. * Key Deliverables: * Assess current Make\-based build, test, dependency, toolchain, and hardware workflows, then define a phased Bazel migration strategy and rollout model. * Design and implement reusable Bazel rules, macros, toolchains, platforms, configuration patterns, and repository standards for embedded software. * Migrate embedded applications, libraries, generated code, firmware, cross\-compilation flows, and platform variants while ensuring build parity and reproducibility. * Integrate Bazel with enterprise CI/CD, testing, release, artifact, deployment, observability, security, and infrastructure workflows. Optimize and operationalize the platform through caching, parallelism, reliability practices, documentation, training, legacy Make retirement, and continuous improvement. * * Target repositories migrated with validated build and test parity. * Reduced clean and incremental build time, CI queue time, and developer feedback time. * Increased reproducibility, approved hermetic\-toolchain adoption, cache effectiveness, and CI capacity. * Lower build, pipeline, and flaky\-test rates, with improved diagnosis and recovery time. * Complete artifact provenance, test evidence, and security\-policy compliance for releases. Strong developer adoption, reduced support burden, and measurable productivity improvement. * GM DOES NOT PROVIDE IMMIGRATION\-RELATED SPONSORSHIP FOR THIS ROLE. DO NOT APPLY FOR THIS ROLE IF YOU WILL NEED GM IMMIGRATION SPONSORSHIP NOW OR IN THE FUTURE. Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all. General Motors is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers. Work Location: Markham, ON, Canada Availability: Full time

Job Title: Machine Learning Engineer Company: Zurich Canada Job Category: Machine Learning Roles & Responsibilities: Are you looking for a caring, collaborative, values\-driven workplace with inspiring teammates and leaders? Do you have the ambition and desire to be the best and thrive at the most impactful global insurance provider in the world? Look no further than Zurich Canada. Zurich Canada is expanding its AI Engineering capability and is looking for Machine Learning / AI Engineers to design, develop and operationalize scalable AI and machine learning solutions. What you will do Machine Learning Engineer \- Applied AI * Build/productionize predictive ML/AI: classification, regression, forecasting and clustering. * Build feature pipelines; establish training, validation/testing and bias/fairness testing. * Evaluate models; move experiments to production and optimize inference. * Assess approved A/B, shadow or controlled pilots; monitor data quality, performance/drift and troubleshoot production issues. * Document assumptions, limitations, versions, training\-data references and approvals. Machine Learning Engineer \- Generative AI * Engineer, evaluate and productionize enterprise GenAI using foundation models, retrieval and agentic patterns. * Build LLM services and RAG pipelines covering ingestion, parsing, cleaning, chunking, embeddings, indexing/retrieval. * Evaluate keyword, semantic\-vector/hybrid search, filtering/reranking; design prompts, structured outputs/context management. * Improve groundedness through retrieval quality, grounding checks, citations, abstention and human review. * Build controlled agentic workflows/tool integrations; evaluate retrieval, answers, safety, agent behaviour/business outcomes. * Monitor quality, groundedness, safety, latency, reliability/cost; apply access\-aware retrieval, sensitive\-data controls and prompt\-injection defences. * Maintain auditable model, prompt, data, index and evaluation records. Machine Learning Engineer \- Data \& ML Platforms * Build/operate enterprise\-scale data, feature and engineering foundations for ML/AI. * Develop training and batch/real\-time inference pipelines, reusable feature frameworks and batch/streaming components. * Optimize Spark/distributed processing; build secure data\-platform/AI interfaces and reusable libraries/templates. * Implement ML dataset quality monitoring; support feature management, lineage/reproducibility. * Engineer large\-scale structured/unstructured data; deploy, monitor and troubleshoot production ML data pipelines. MLOps Engineer * Build/operate platforms, automation and controls across the ML/AI lifecycle. * Design CI/CD for models/AI applications; establish model registration, versioning, lineage/promotion. * Build reproducible training/deployment environments; support staged releases, shadow deployments/rollback. * Monitor health, latency, data quality, model performance/drift; develop retraining/redeployment workflows with validation/approvals. * Manage ML infrastructure/configuration; implement access controls, audit trails/governance evidence and reusable MLOps standards. * Python and SQL skills. * Software engineering fundamentals including Git, APIs, testing and CI/CD. * Understanding of ML concepts and the model\-development lifecycle. * Experience with data processing and analytical workloads. * Experience in cloud\-based development environments. * Understanding of reliable, maintainable, production\-ready solutions. * Databricks, MLflow and Apache Spark/PySpark. * Microsoft Azure or equivalent AWS/Google Cloud technologies. * Azure DevOps or GitHub. * Docker and containerized applications. * REST APIs. * scikit\-learn, PyTorch, TensorFlow or comparable ML/deep\-learning frameworks. * Azure OpenAI or comparable managed AI platforms. * RAG, embeddings, retrieval and LLM evaluation. * Infrastructure as code, Kubernetes and production observability. * Security, privacy, Responsible AI and model governance in a regulated environment. Intermediate * Independently design/deliver ML/AI components and solutions. * Own development through production implementation. * Make appropriate engineering and technology choices. * Troubleshoot complex data, model and production issues. * Contribute to architecture and engineering standards. * Mentor junior team members. * Work with stakeholders to refine technical requirements. Senior * Lead design/engineering of complex enterprise AI/ML solutions. * Make architecture and technology decisions. * Establish reusable patterns and engineering standards. * Lead production\-readiness, scalability, reliability and security decisions. * Mentor engineers and provide technical leadership. * Drive engineering excellence through design/code reviews. * Partner with architecture, security, governance and business leadership. * Evaluate emerging AI technologies and appropriate enterprise adoption patterns. We value diverse perspectives and foster a collaborative environment where employees are empowered to make an impact. We offer a comprehensive rewards package designed to support employee well\-being, growth, and success. * Comprehensive health and wellness benefits. * Minimum four weeks of vacation annually. * Four personal days each year to support personal, cultural, religious, or well\-being needs. * Access to ongoing learning and development opportunities. * Opportunities to support and give back to our communities. * Recognition as one of Greater Toronto's Top Employers and recipient of Insurance Business Canada's 5\-Star Diversity, Equity and Inclusion Award. Make a difference. Be challenged. Be inspired. Be supported. Love what you do. Work for us. A future with Zurich Now is the time to move forward and make a difference. At Zurich, we want you to share your unique perspectives, experiences and ideas so we can grow and drive sustainable change together. As part of a leading global organization, Zurich North America has 0 years of experience managing risk and supporting resilience. We are a leading provider of commercial property\-casualty insurance solutions and a wide range of risk management products and services for businesses and individuals. Today, we serve more than 25 industries, from agriculture to technology and insure 90% of the Fortune 500®. Our growth strategy is not limited to our business. As an employer, Zurich strives to provide ongoing career development opportunities and foster an environment where voices are diverse, behaviors are inclusive, actions drive equity, and our people feel a sense of belonging. Be a part of the next evolution of the insurance industry. Join us in building a brighter future for our people, our customers and the communities we serve. Only applicable for Canada: For Zurich Canada's commitment to diversity and accessibility please click here. If you would prefer to not receive future electronic messages from Zurich Insurance Company Ltd's recruitment management system, please email your request to have your job profile deleted from the system by clicking here. Zurich Insurance Company Ltd 100 King St., W., Suite 5500, Toronto, ON, M5X 1C9\. www.zurichcanada.com Work Location: Waterloo, Ontario, Canada Availability: Full time

Job Title: Staff DevOps Engineer Company: Terawatt Infrastructure Job Category: Machine Learning Roles & Responsibilities: The once in a century transition to autonomous and electric vehicles is underway and will require a multi\-trillion\-dollar investment in energy and charging infrastructure, and the real estate to site it on. Terawatt is the leader in delivering large scale, turnkey charging solutions for companies rapidly deploying AV and EV fleets. Whether it’s an urban mobility hub, or a carefully located multi\-fleet hub for semi\-trucks, Terawatt brings the talent, capabilities, and capital to create reliable, cost\-effective solutions for customers on the leading edge of the transition to the next generation of transport. With a growing portfolio of sites across the US in urban hubs and along key logistics and transportation corridors. Terawatt is building the permanent transportation and logistics infrastructure of tomorrow through a robust combination of capital, real estate, development, and site operations solutions. The company develops, finances, owns, and operates charging solutions that take the cost and complexity out of electrifying fleets. Terawatt is not a traditional infrastructure operator. Our technology platform transforms a portfolio of sites into a reliable, intelligent network — through advanced power management, operational optimization, and data\-driven systems that back our customers with hard performance guarantees. That's what makes us a de\-risked operator and a category\-defining company. ### Role Description Terawatt's headquarters is located in San Francisco, CA; this is a remote role where candidates must live in the Greater Toronto, ON Area.* Join Terawatt’s innovative technology team as a Staff DevOps Engineer and help drive the evolution of our platform to support one of the leading fleet EV charging solutions in North America. In this role, you will lead the development and reliability of Terawatt’s charging network management system and the capabilities that enable a high\-quality site experience for customers. Working closely with the SVP of Technology, the Product team, and other technical partners, you will play a key role in expanding our platform and delivering meaningful value in a rapidly evolving industry. This role will help scale our cloud infrastructure and support organizational growth by implementing best practices that improve the reliability, performance, and maintainability of our charging infrastructure and software systems. You will also own the infrastructure behind Terawatt's internal tools and AI platform, partnering with our AI Product Manager and engineers to deploy, secure, observe, and scale agentic workflows across the company. ### Core Responsibilities * Set technical direction for DevOps and platform engineering, mentor engineers, and champion infrastructure standards across the organization. * Lead planning for team goals that align with overall business goals and technology roadmap * Lead and architect the evolution of our cloud infrastructure using Terraform, building resilient and scalable systems to support business growth. * Maintain helm charts and deployment patterns that enable teams to manage the lifecycle of their services while adhering to established deployment standards. * Build tooling to enable engineering teams to own the application deployment process through CI/CD pipelines using GitHub Actions. * Drive security across every layer of the stack, using industry\-standard tools to detect vulnerabilities and anomalies and automating SOC 2 compliance controls. * Extend security controls to AI and agentic systems, covering risks such as prompt injection, over\-permissioned tool access, and sensitive data exposure. * Advance observability with OpenTelemetry and Grafana Cloud across services, infrastructure, and AI workloads. * Build developer tooling for local and remote container\-based development, plus automated production\-like scenarios for testing and release validation. * Build and operate infrastructure for ML and internal AI workloads, including compute for model training, hosting for agents and MCP servers, and least\-privilege access to internal data. * Partner with the Data team on core data infrastructure, including our Databricks data lake and Kafka event streams (Aiven/AWS). * Contribute to building a highly available, web\-based depot operations platform that supports the future of EV charging using NodeJS. * Participate in a 24/7 on\-call rotation and lead incident response and blameless postmortems. ### Minimum Qualifications * 8\+ years building and operating high\-availability production systems, including leading DevOps, SRE, or platform engineering initiatives. * Deep experience with building and maintaining AWS, managed Kubernetes (EKS), and infrastructure as code (Terraform). * Experience building CI/CD pipelines (e.g., GitHub Actions) and observability with tools such as OpenTelemetry and Grafana. * Experience leading SRE or DevOps initiatives supporting production cloud platforms. * Experience with managed databases such as PostgreSQL or MongoDB. * Strong communication skills and the ability to collaborate effectively across engineering, product, and infrastructure teams. ### Preferred Qualifications We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us. Work Location: Canada Availability: Full time

Job Title: Machine Learning Engineer Company: Point11 Job Category: Machine Learning Roles & Responsibilities: We are a team building the infrastructure for the agent era. A decade ago, the brands that leaned into mobile won. The same shift is happening with agents: how people find businesses, ask questions, and buy is moving from static pages into conversations. 800 million people already discover brands through agent search, and who gets chosen is being decided right now. About You * You've trained and shipped machine learning models that run in production * You're strong in Python and the modern ML stack * You're rigorous about evaluation, baselines, and statistical validity * You can explain a model's behavior to an engineer and to a customer * You're in Toronto or willing to relocate. This role is hybrid, in our Toronto office three days a week. This posting is for an existing vacancy. * Your models decide how faithful our product is * Hybrid in Toronto, in New York's time zone * A founding role in Point11's Canadian team * A direct line to the founding team on product * An annual learning budget for conferences and development Point11 provides equal employment opportunities to current and prospective employees, without regard to race, color, religion, sex, gender identity, national origin, sexual orientation, age, pregnancy, disability, marital status, or any other status protected by the laws of the country where the role is based. Work Location: Greater Toronto Area, Canada Availability: Full time

Job Title: Senior Data Scientist – Applied Machine Learning Company: Lendi Group Job Category: Machine Learning Roles & Responsibilities: Lendi Group is transforming the way Australians find, buy and own property. As the company behind Lendi — Australiaʼs original and \#1 digital mortgage brand — and the iconic Aussie franchise network, we combine technology, distribution and deep property expertise to support customers across their entire property journey. Powered by our proprietary AI platform and a national network of 1,300 brokers and 220 retail stores, Lendi Group now manages a $107B\+ loan book and continues to set the pace in the industry, recently recognised as Aggregator of the Year. Through our integrated Find–Buy–Own ecosystem and industry\-leading Agentic platform, weʼre redefining how property decisions are made — delivering greater confidence, speed and simplicity for customers. This role sits at the centre of that next phase of growth. * Innovation at Our Core – We challenge the status quo and push boundaries to create better solutions, with a goal of becoming AI\-native by June 2026\. * Work with the Best – Collaborate with some of the brightest minds in fintech, financial services, and strategy. * Make an Impact – Contribute to meaningful projects that shape our business and the future of property finance. * Grow \& Evolve – Develop your skills and advance your career in a fast\-moving, purpose\-driven environment. About the role This is a hands\-on role covering the full lifecycle: framing the problem, understanding the data, developing features and models, deploying solutions, monitoring performance and improving them over time. You will work closely with data engineers, product managers, analysts, software engineers and business stakeholders to deliver measurable outcomes. Generative and agentic AI will form part of the team’s evolving toolkit, where it is the right solution to the problem. The core of the role is strong applied machine learning and sound data\-science judgement. Job Description * Translate customer and business problems into clear analytical and machine\-learning objectives. * Work with large datasets, event data and feature stores to identify useful signals and build predictive features. * Develop, evaluate and improve models for use cases such as propensity, personalisation, growth and retention. * Apply appropriate techniques across classification, regression, experimentation, forecasting and other applied data\-science problems. * Take models through the full product lifecycle, including deployment, automation, monitoring, retraining and ongoing maintenance. * Help improve data quality, feature pipelines, model monitoring, drift detection and ML Ops practices. * Work with product managers and business stakeholders to define success measures and translate model outputs into action. * Explain technical approaches, assumptions and results clearly to technical and non\-technical audiences. * Collaborate with data, software and AI engineering teams to review solutions, improve coding standards and share knowledge. * Contribute to technical documentation, design discussions and delivery planning. * Work with external partners or vendors where required to deliver the right solution. * A vibrant, relaxed, yet professional culture. * Hybrid working arrangement designed to support work\-life balance, while fostering meaningful connection and collaboration. * A holistic wellbeing programs offering 24/7 support, including medical, mental health, and financial wellbeing services to enable our workforce to thrive at home and work. * Generous paid Parental Leave: we celebrate our growing Lendi Group family with 18\-26 weeks leave for primary carers and up to 4 weeks for secondary carers. * An additional week’s Loyalty Leave each year after reaching 3 years’ service. * Wellness initiatives with a strong focus on psychological safety. We’re committed to fostering a diverse and inclusive community at Lendi Group. We believe that a team reflecting the world around us leads to greater innovation, stronger collaboration, and a more engaging workplace. Work Location: Sydney, New South Wales, Australia Availability: Full time

Job Title: Senior Machine Learning Engineer Company: Atlassian Job Category: Machine Learning Roles & Responsibilities: Overview Working at Atlassian Atlassians can choose where they work—whether in an office, from home, or a combination of the two. That way, Atlassians have more control over supporting their family, personal goals, and other priorities. We can hire people in any country where we have a legal entity. Responsibilities Your future team You will join AI Context, a team of software and machine learning engineers working across Sydney, Melbourne, Brisbane, and the US West Coast. The team has a mix of SWEs and MLEs and partners closely across Rovo \+ AI and product teams. You will act as a thought partner to Engineering Managers and Heads of Engineering, influence technical direction across stakeholder teams, and lead small virtual squads that own critical components. You will also coach junior engineers and help the team achieve its key results. Work Location: Greater Brisbane Area Availability: Full time

Job Title: Associate Deployment Engineer - Galaxy Graduate Program Company: Celonis Job Category: Machine Learning Roles & Responsibilities: Celonis is the trusted platform to industrialize Enterprise AI. At our core is the Celonis Context Model — which combines process data, business knowledge, and intelligence into a living digital twin of the enterprise that AI can actually understand, turning AI's operational blind spots into operational clarity. World's leading companies trust Celonis and its global ecosystem of partners to make their AI agents, people, systems, and processes work together, achieving transformational outcomes. We believe there's a massive opportunity to unlock global productivity and sustainability by giving AI the context to understand how every business process really works. Join our mission to make processes work for people, companies, and the planet. The Team Celonis makes processes work for people, companies, and the planet. As the Celonis Services organization, we are the strategic implementation consulting \& transformation arm of a unified Customer Organization aligned to four core mandates: We deliver production\-ready Celonis Platform implementations that drive measurable top, bottom, and green\-line impact. Moving beyond “point\-in\-time” analysis, we utilize a Discover\-and\-Build approach to solve the world's most complex operational challenges. We don't just implement AI for our customers; we live it. Our project delivery lifecycle is accelerated by state\-of\-the\-art AI augmentation , allowing our consultants to focus on high\-level, strategic problem\-solving. By serving as the eyes and ears in the field, we maintain a continuous innovation loop with our Product \& Engineering teams, ensuring our frontline learnings directly shape the future of the Celonis Platform. The Role As an Associate Deployment Engineer within the Galaxy Graduate Program , you will support the end\-to\-end Discover\-and\-Build journey for our global customers. The Galaxy program unites Celonauts across different locations into one dedicated onboarding program which develops recent graduates into well rounded, skilled Services professionals in 12 months. As part of a consulting team, collaborating with more experienced consultants, you will bridge the gap between complex data landscapes and strategic business value. This role is designed for high\-potential university graduates who possess a Business\-Critical Mindset and the ability to understand how technical solutions can impact customer operations and improve efficiency, resulting in platform adoption and long\-term ROI for our customers. * Support Strategic Implementations: Support the implementation of Celonis Platform as a business\-critical tool by connecting customer data to actionable strategic outcomes. * Execute Discover\-and\-Build: As part of a project team, participate in process mining discovery activities, data transformation (SQL/Python), and the creation of AI\-driven analyses to identify execution gaps. * AI\-Forward Solutioning: Leverage your technical background to build and deploy AI\-forward solutions, utilizing Machine Learning and LLM integrations for our most strategic customers. * Stakeholder Engagement: Actively participate in discovery and requirement workshops, practicing a consulting mindset to communicate technical findings to business stakeholders and continue building the solution with a strong customer centric mindset. * Operational Excellence: Contribute to project speed and efficiency by maintaining high\-quality documentation and ensuring Built\-in Quality Control in every line of code or analysis produced. * Cross team collaboration: Have the opportunity to collaborate with various teams within the Celonis organization, including but not limited to: + Business Analytics, Academy and Global Programs + Business Apps \& Product and Engineering + Solution Architecture \& Celonis Support What Celonis can offer you: * Pioneer Innovation: Work with the global leader in Process Mining and the Process Intelligence Graph to shape the future of AI\-driven business operations. * Ownership from Day 1: Every full\-time Celonaut is an owner, receiving Restricted Stock Units (RSUs) and merit\-based refresh grants. * Unrivaled Family Support: Benefit from our inclusive parental leave policy—24 weeks of fully paid leave for primary carers and 12 weeks for supporting carers, available from your first day of employment. * Work\-Life Integration: Enjoy Unlimited PTO (in applicable regions) and generous PTO globally, as well as a flexible hybrid work model that balances remote focus with vibrant office collaboration. * Continuous Growth: Elevate your skills through our 70\-20\-10 learning framework, mentorship programs, and access to a dedicated learning platform. * Holistic Well\-being: Prioritize your health with subsidized Wellhub memberships, mental health counseling, and dedicated Wellness Weeks that prioritize work/life balance. * Drive Sustainability: Participate in annual Impact Days, where you receive paid time off to volunteer for community and environmental causes with your local office, or virtually. * Global Inclusion \& Belonging: Find community through our Inclusion Think Tank and participate in our annual Inclusion Days, ensuring every voice is heard and valued. * Value\-Driven Impact: Join a mission\-led organization where our core values—Live for Customer Value, The Best Team Wins, We Own It, and Earth Is Our Future—drive every decision. About Us: Celonis is the trusted platform to industrialize Enterprise AI, empowering organizations to analyze, design, and operate AI\-driven processes. The Celonis Platform is powered by the Celonis Context Model, which combines process data, business knowledge, and intelligence to create a living digital twin of the enterprise that AI can understand — turning AI’s operational blind spots into operational clarity. Industry\-leading companies around the world trust Celonis and its global ecosystem of partners to make their AI agents, people, systems, and processes work together, achieving transformational outcomes. Celonis is headquartered in Munich, Germany, and New York City, USA, with more than 20 offices worldwide. Use of Artificial Intelligence Tools We rely on an artificial intelligence tool to match the information from your resume to the relevant Celonis job descriptions. This processing is limited to the information provided in your resume or in your candidate profile. The tool produces a match score per candidate for a role, suggests preliminary ranking, and provides recommendations. The tool is only used for support in parts of the job application process, including to facilitate the identification of the relevant Celonis Jobs for candidates and recruiters. All final decisions are made by hiring managers and the Celonis talent acquisition team. Hiring managers and HR specialists use this tool responsibly, are aware of the risk of potential bias, and are equipped to mitigate it. Work Location: Greater Bengaluru Area Availability: Full time

Job Title: Senior_Expert (AI_Engineering) Company: Novartis India Job Category: Machine Learning Roles & Responsibilities: Relocation Support: Yes Imagine shaping how breakthrough medicines are discovered by bringing cutting\-edge AI from concept to real\-world application. As a Senior Expert in AI\-Engineering, you will sit at the critical intersection of innovation and delivery—transforming advanced machine learning models into scalable, reliable solutions that accelerate drug discovery. Collaborating with leading scientists and AI experts, you will drive the translation of pioneering research into impactful tools, ensuring models are reproducible, efficient, and ready to solve complex biomedical challenges. This is an opportunity to directly influence how modern AI reshapes scientific discovery and improves patient outcomes. About The Role Key Responsibilities Why Novartis: Helping people with disease and their families takes more than innovative science. It takes a community of smart, passionate people like you. Collaborating, supporting and inspiring each other. Combining to achieve breakthroughs that change patients’ lives. Ready to create a brighter future together? https://www.novartis.com/about/strategy/people\-and\-culture Work Location: Greater Hyderabad Area Availability: Full time

Job Title: Manager - IT Program Management Company: Charles Schwab Job Category: Machine Learning Roles & Responsibilities: Hyderabad, Telangana Requisition ID 2026\-128257 Category Project Management, Product Management Position type Regular Our Hyderabad location is central to Schwab’s growth, bringing together talented people and technology to drive innovation, scale and efficiency. Here, you will work alongside teams who create solutions that support millions of clients every day. The work you do is more than daily operations – it’s a chance to experiment, learn, and build within a values\-driven, supportive environment. This is a unique opportunity to be part of our early growth phase and shape something new, backed by the stability and strength of a Fortune 500 company. Your impact begins on day one, and your contributions will help define our future in the region The Schwab Asset Management (SAM) Technology organization is a part of Schwab Technology Services that is responsible for Schwab's investment management, operations, data, and research platforms. Everything that SAM Tech builds serves Schwab’s mission of helping clients reach their financial goals. As a Quantitative Analyst \- Investment Research in the SAM Investment Research Technology group, you will play a critical role in delivering cutting\-edge research and product development capabilities designed to advance SAM business opportunities and to support the Schwab Center for Financial Research (SCFR) in its mission to provide clients and advisors actionable investment advice. We curate structured and unstructured datasets for both exploratory and product\-focused research, and we implement and maintain investment models across multiple asset classes and product categoriess, including equity and fund ratings, thematic investing baskets, multi\-asset solutions, factor strategies, and more. This role will interact with researchers and other business users to help bring together data, analytics, modeling, and operational capabilities into a common ecosystem for all research teams. You will help establish the foundational capabilities, frameworks, and workflows that enable innovative research products, accelerate time\-to\-market, and promote greater reuse of data and technology assets across the organization. This is an opportunity to help define the future state of quantitative research technology at Schwab. Work Location: Telangana, India Availability: Full time

Job Title: Senior Machine Learning Engineer(Growth & ML), Hyderabad Company: Warner Bros. Discovery Job Category: Machine Learning Roles & Responsibilities: Warner Bros. Discovery, a premier global media and entertainment company, offers audiences the world's most differentiated and complete portfolio of content, brands and franchises across television, film, streaming and gaming. The new company combines Warner Media’s premium entertainment, sports and news assets with Discovery's leading non\-fiction and international entertainment and sports businesses. , and we are an early, enthusiastic adopter of agentic AI development workflows. About the Role As a Senior MLE, you will own the design and delivery of production ML systems that directly impact audience targeting, advertising revenue, subscriber engagement, and retention across WBD’s global portfolio. You will lead technical execution on key workstreams — including probabilistic identity resolution, lookalike modeling, single\-title affinity, and forecasting — while mentoring MLE 2s and collaborating closely with Staff MLEs and product stakeholders. This is a high\-ownership role for engineers with roughly 1-2 years of experience who can independently drive a project from problem framing through production deployment and monitoring. Roles \& Responsibilities: * Lead end\-to\-end development of production ML systems: data sourcing, feature engineering, model training, evaluation, deployment, and monitoring. * Own key ML products such as probabilistic identity resolution (matching unauthenticated device IDs and 1P cookies to households/persons with calibrated confidence), single\-title affinity (e.g., STAT two\-tower retrieval), and audience/propensity models. * Design scalable feature pipelines on Databricks (PySpark, Delta, Workflows/DLT, Unity Catalog) and the WBD feature store, with documented feature contracts, backfill paths, and freshness SLAs. * Architect batch and near\-real\-time inference pipelines integrated with Snowflake and activation systems (Mosaic, FreeWheel, GAM). * Develop and optimize models across the ML spectrum: gradient boosting (XGBoost/LightGBM), embedding/two\-tower retrieval, neural ranking, probability calibration (e.g., isotonic regression), and probabilistic/graph\-based matching. * Design rigorous offline and online experiments; define evaluation frameworks (precision/recall, AUC\-ROC, NDCG, decile lift, calibration curves) appropriate to each use case. * Apply causal\-inference techniques (propensity scoring, uplift/incrementality modeling) to measure true lift of audience targeting on engagement and retention KPIs. * Contribute to lookalike modeling (LAL 2\.0\+) using 1,000\+ first\- and third\-party features, including privacy\-safe builds inside Data Clean Rooms (Snowflake DCR). * Champion MLOps best practices: model versioning, champion/challenger promotion, automated retraining triggers, drift detection, and production monitoring with MLflow on Databricks. * Build and maintain robust, reproducible, auditable ML pipelines on Databricks (and AWS SageMaker where appropriate, e.g., the identity\-resolution track); enforce leakage prevention and training/serving consistency. * Contribute to the team’s feature\-store strategy — feature contracts, backfills, and freshness SLAs — and implement data\-quality checks, model\-health dashboards, and alerting thresholds. * Embed FinOps cost discipline (compute caps, auto\-termination, job tagging) into pipeline design. We embrace the opportunity to build a workforce that reflects a wide array of perspectives, backgrounds and experiences. Being an equal opportunity employer means that we take seriously our responsibility to consider qualified candidates on the basis of merit. In line with the laws of the country or region in which the role is based, this includes consideration without regard to race, color, ethnicity, national origin, citizenship status, religion or belief, sex, gender, gender identity or expression, sexual orientation, age, marital status, pregnancy, parenthood, physical or mental disability, genetic information, military or protected veteran status, union status or any other category protected by applicable law. Work Location: Greater Hyderabad Area Availability: Full time