Job Title: ML Engineer II Company: UST Job Category: Machine Learning Roles & Responsibilities: Role description "We are seeking a Senior/Lead Agentic AI Engineer with 8\-10\+ years of experience to design, architect, and deliver enterprise\-scale Agentic AI solutions. Required Skills: Strong expertise in Agentic AI, Multi\-Agent Systems, LLMs, RAG, Tool Calling, Planning \& Reasoning. Hands\-on experience with LangGraph, LangChain, Semantic Kernel, CrewAI, AutoGen, MCP, Azure AI Foundry. Strong software engineering background with Python, C\#, Java, TypeScript, or Go. Experience with Cloud (Azure/AWS/GCP), Microservices, Kubernetes, APIs, Vector Databases. Ability to lead solution design, architecture discussions, and mentor development teams. Preferred: Strong hands\-on .NET Core / C\# development experience. Experience leading enterprise AI/GenAI implementations." Work Location: Karnataka, India Availability: Full time
Job Title: Applied AI Engineer Sales Force - Software Engineer II Company: Deloitte Job Category: Machine Learning Roles & Responsibilities: Summary Position Summary Applied AI Engineer I Role Overview: As a Salesforce Applied AI Engineer I , you will actively engage in your engineering craft, taking a hands\-on approach to building and enhancing high\-visibility, full\-stack products that serve the business and its users. Your expertise will be pivotal in delighting customers and users, while driving tangible value across Deloitte’s product and AI investments. You will leverage your extensive engineering craftsmanship across full\-stack software engineering and modern frameworks—together with applied AI fluency that lets you build GenAI and agentic capabilities directly into the products you deliver—consistently demonstrating your strong track record in delivering high\-quality, outcome\-focused solutions. The ideal candidate will be a dependable team player, collaborating with cross\-functional teams to design, build, and ship products end to end, from concept through production. Key Responsibilities: * Embrace and drive a culture of accountability for customer and business outcomes—and for the cost of achieving them. Develop engineering solutions that solve complex problems with valuable outcomes, ensuring high\-quality, lean designs and implementations, and owning the inference, token, and cloud cost of what you build. * Serve as the technical advocate for products, ensuring code integrity, feasibility, and alignment with business and customer goals. Lead requirement analysis, component design, development, testing, integrations, and support. * Maintain accountability for code\-design integrity, implementation fidelity to architecture and tech stack, quality, data, and ongoing maintenance and operations. Be hands\-on, self\-driven, and continuously learn new approaches, languages, and frameworks. Create technical specifications, and write high\-quality, supportable, scalable code ensuring all quality KPIs are met or exceeded. Demonstrate collaborative skills to work effectively with diverse teams. * Develop lean engineering solutions through rapid, inexpensive experimentation to solve customer needs. Engage with customers and product teams before, during, and after delivery to ensure the right solution is delivered at the right time. * Adopt a mindset that favors action and evidence over extensive planning. Utilize a leaning\-forward approach to navigate complexity and uncertainty, delivering lean, supportable, and maintainable solutions. * Work collaboratively with empowered, cross\-functional teams including product management, experience, and delivery. Integrate diverse perspectives to make well\-informed decisions that balance feasibility, viability, usability, and value. Foster a collaborative environment that enhances team synergy and innovation. * Possess expertise in modern software engineering practices and principles, including AI and Agentic SSDLC to deliver daily product deployments using full automation from discovery to production to operations with all quality checks through SSDLC lifecycle. Strive to be a role model, leveraging these techniques to optimize solutioning and product delivery. Demonstrate strong understanding of the full lifecycle product development, focusing on continuous improvement and learning. * Quickly acquire domain\-specific knowledge relevant to the business or product. Translate business/user needs, architectures, and UX/UI designs into technical specifications and code. Be a valuable, flexible, and dedicated team member, supportive of teammates, and focused on quality and tech debt payoff. * Exhibit exceptional communication skills, capable of articulating complex technical concepts clearly and compellingly. Inspire and influence teammates and product teams through well\-structured arguments and trade\-offs supported by evidence. Create coherent narratives that align technical solutions with business objectives. * Engage and collaborate with product engineering teams at all organizational levels, including customers as needed. Build and maintain constructive relationships, fostering a culture of co\-creation and shared momentum towards achieving product goals. Align diverse perspectives and drive consensus to create feasible solutions. The team: US Deloitte Technology Product Engineering has modernized software and product delivery, creating a scalable, cost\-effective model that focuses on value/outcomes that leverages a progressive and responsive talent structure. As Deloitte’s primary internal development team, Product Engineering delivers innovative digital solutions to businesses, service lines, and internal operations with proven bottom\-line results and outcomes. It helps power Deloitte’s success. It is the engine that drives Deloitte, serving many of the world’s largest, most respected companies. We develop and deploy cutting\-edge internal and go\-to\-market solutions that help Deloitte operate effectively and lead in the market. Our reputation is built on a tradition of delivering with excellence. Professional development At Deloitte, professionals have the opportunity to work with some of the best and discover what works best for them. Here, we prioritize professional growth, offering diverse learning and networking opportunities to help accelerate careers and enhance leadership skills. Our state\-of\-the\-art DU: The Leadership Center in India, located in Hyderabad, represents a tangible symbol of our commitment to the holistic growth and development of our people. Explore DU: The Leadership Center in India . Work Location: Bengaluru, Karnataka, India Availability: Full time
Job Title: MS - FDL - Senior Manager - AI Architect Company: EY Job Category: Machine Learning Roles & Responsibilities: Job Title: Senior Manager – AI Architect We are looking for a highly skilled and experienced Senior Manager – AI Architect to lead the strategy, architecture, and governance of enterprise AI solutions supporting data products and corporate finance transformation. This role combines AI/ML architecture, technical leadership, and people management, translating business needs into secure, scalable, and responsible AI solutions. The ideal candidate will integrate predictive machine learning, generative AI, and appropriately controlled agentic workflows with enterprise applications and data to enable transformation across P2P, O2C, R2R, and FP\&A. You will own AI architecture quality and technology roadmaps across engagements, lead architects and technical specialists, and partner with data science, engineering, product, security, risk, and business teams to guide solutions from discovery through production adoption and measurable value realization. Responsibilities: AI Strategy \& Architecture Leadership * Provide architecture oversight across AI initiatives, defining acceptance criteria, technical dependencies, delivery risks, and stage gates from experimentation through production readiness. * Partner with engineering and platform teams to establish MLOps and LLMOps practices, including versioned datasets, models and prompts, reproducible evaluation, deployment controls, and rollback. * Define task\-specific evaluation frameworks covering predictive performance, groundedness, retrieval quality, hallucination risk, robustness, fairness where relevant, latency, and cost; validate against representative test data and business baselines. * Design production monitoring for data and model drift, output quality, reliability, usage, and inference spend; establish fallback behavior, incident response, and controlled model or provider updates. * Embed responsible AI, privacy, security, and applicable compliance controls with risk and legal teams, including data provenance, audit trails, prompt\-injection defenses, sensitive\-data protection, and risk\-based human oversight. Team Leadership \& Talent Management * Lead and scale an AI architecture team, coordinating data scientists, ML engineers, data engineers, and application specialists across engagements; develop architects and technical leads. * Build an inclusive, high\-performance AI practice focused on rigorous experimentation, responsible innovation, reusable knowledge, and measurable business outcomes. * Own hiring, resource planning, performance management, succession planning, and capability development aligned with AI delivery demand and evolving technology needs. * Mentor architects and technical specialists on AI design, evaluation rigor, production readiness, stakeholder influence, and career growth; strengthen peer reviews and communities of practice. Business \& Stakeholder Management * Partner with finance transformation leaders, product owners, and clients to identify AI opportunities, clarify process constraints, and define measurable success criteria. * Present AI solution options, limitations, investment needs, and risk trade\-offs to decision\-makers; align expectations on automation boundaries, human review, and business value. * Lead AI architecture inputs for proposals, RFP responses, and demonstrations, including solution narratives, prototypes, estimates, data requirements, and implementation assumptions. * Communicate architecture decisions, evaluation results, residual risks, adoption readiness, and realized business impact clearly to executive and technical audiences. * Develop reusable AI reference designs, evaluation suites, retrieval components, model integration patterns, and governance templates to accelerate consistent delivery. * Assess emerging AI capabilities through structured experiments and business cases; scale only where evidence supports performance, operational feasibility, and acceptable risk. * Enable finance\-focused capabilities such as document intelligence, knowledge assistants, forecasting, and anomaly detection, with traceable outputs and controls appropriate to each use case. Leadership \& Behavioral Skills * Strong people leadership, practice development, and coaching skills, with the ability to lead architects and influence data science, engineering, and business teams. * Excellent stakeholder management and communication skills, including executive\-level engagement and the ability to explain AI capabilities, limitations, and risks without overstating results. * Ability to balance AI strategy with pragmatic implementation, challenge assumptions using evidence, and make sound decisions amid rapidly evolving technology. * High ownership mindset focused on responsible AI adoption, production reliability, solution quality, and measurable business outcomes. Work Location: Karnataka, India Availability: Full time
Job Title: Staff Machine Learning Engineer Company: Warner Bros. Discovery Job Category: Machine Learning Roles & Responsibilities: Roles \& Responsibilities * Own the architecture and roadmap of the model serving runtime, supporting multiple ML frameworks and inference engines behind one control plane * Lead large\-scale migrations and rollouts of production models onto the platform with zero viewer\-facing regressions * Build and maintain serving backends, model configurations and batching strategies that meet strict tail\-latency targets at high request volume * Design autoscaling, capacity management and multi\-region resilience for latency\[1]critical serving across Max, Discovery\+ and other WBD offerings * Drive observability, cost optimization and performance tuning across the serving fleet, including hardware selection, GPU and CPU utilization, and model optimization * Define the contract between model training and serving so a validated model artifact deploys to production through standard, automated paths * Establish per\-model SLOs with model owners and build the telemetry that proves them * Collaborate with applied scientists, partner engineering teams and the core infrastructure team as the platform onboards new models, runtimes and markets * Author, test, review and optimize production\-level code in Python while executing best practices in version control, CI/CD and code integration * Take part in the platform on\-call rotation and lead incident reviews that result in design changes, not just fixes * Contribute design documents and technical documentation to support architecture decisions, knowledge transfer and sharing * Mentor engineers, raise the bar in design and code reviews, and represent the platform in cross\-team architecture decisions * 9\+ years of industry experience * 5\+ years of experience building or operating production ML infrastructure or comparable low\-latency, large\-scale distributed systems with a large customer base * Hands\-on experience running model inference in production at scale * Strong Kubernetes fundamentals and experience running GPU and CPU workloads on it * Proven performance engineering skills: profiling, tail\-latency analysis, batching and concurrency under load * 7\+ years of programming experience in Python, plus working fluency in a systems language such as C\+\+, Go or Rust * Good practical knowledge of the modern machine learning lifecycle, from training artifacts through deployment, rollout and monitoring * Strong architectural and design skills, with a track record of leading multi\-quarter technical initiatives across teams * Operational maturity: experience owning a tier\-1 service, including on\-call * Experience with one of the cloud platforms AWS/GCP/Azure, Docker and Kubernetes, and CI/CD tools like GitHub Actions, Jenkins etc. * Excellent written and verbal communication skills; comfortable contributing to technical documentation and on\-call support * Ability to technically collaborate with partners across time zones 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: Karnataka, India Availability: Full time
Job Title: Senior Machine Learning Engineer Company: Quantiphi Job Category: Machine Learning Roles & Responsibilities: Good To Have Skills * Hands\-on experience with OCR/Document Intelligence engines and NLP techniques for extracting structured information from documents and images. * Hands\-on experience with Bedrock Agentcore * Hands\-on experience with OpenAI, Anthropic, Gemini, or other foundation models. * Experience with Docker, Kubernetes, and MLOps practices. * Experience with Redshift, SQL, DynamoDB, or AWS Glue. * Exposure to model monitoring, evaluation, and observability for GenAI applications. * Ability to work in an Agile and DevOps environment. Work Location: Bengaluru, Karnataka, India Availability: Full time
Job Title: AI and ML Engineer Company: Sandisk Job Category: Machine Learning Roles & Responsibilities: Sandisk meets people and businesses at the intersection of their aspirations and the moment, enabling them to keep moving and pushing possibility forward. We do this through the balance of our powerhouse manufacturing capabilities and our industry\-leading portfolio of products that are recognized globally for innovation, performance and quality. Description We are seeking a talented AI/ML Engineer in Data and AI team to drive the design, development, and operationalization of machine learning and GenAI solutions across Sandisk's enterprise. In this role, you will own end\-to\-end AI/ML projects, from problem framing and data strategy through model deployment and monitoring. You will partner directly with business stakeholders to translate complex requirements into scalable, production\-grade solutions and mentor junior engineers on the team. Key Responsibilities * Design, develop, and implement machine learning models and statistical analyses to address manufacturing, supply chain, and product quality challenges. * Conduct exploratory data analysis and present actionable insights and recommendations to stakeholders. * Develop prompt engineering strategies and feedback loops for LLM optimization; capture and normalize LLM interactions into reusable Knowledge Artifacts. * Implement Retrieval\-Augmented Generation (RAG) pipelines, including document parsing, chunking, vectorization, and semantic search using embeddings and vector databases. Support domain\-specific ontologies, taxonomies, governance and versioning. * Support agentic workflows using industry\-standard frameworks for autonomous task orchestration and multi\-step reasoning, with safe and controlled execution via constraints, policies, and fallback paths. * Contribute to establishing and maintaining data quality standards, implementing validation frameworks and monitoring systems. * Support the deployment and monitoring of machine learning models in production environments, including performance tracking and drift detection. * Stay current with emerging data science technologies, methodologies, and industry trends, evaluating their applicability to organizational needs. * Support end\-to\-end project delivery, ensuring timely completion and alignment with business objectives. * Experience with Large Language Models (LLMs), prompt engineering, and GenAI application development. * Familiarity with vector databases, embedding models, and semantic search architectures. * Experience building agentic AI workflows and multi\-LLM orchestration systems. * Hands\-on experience with data visualization and business intelligence tools such as Tableau, Power BI, or equivalent platforms. * Experience using version control systems (Git) and collaborative software development practices. * Experience deploying, monitoring, or maintaining machine learning models in production environments. * Familiarity with cloud platforms (Azure, AWS, or GCP) and Lakehouse architectures (e.g., Databricks). Work Location: Bengaluru, Karnataka, India Availability: Full time
Job Title: Lead Data Scientist Company: Ecolab Job Category: Machine Learning Roles & Responsibilities: Role Summary As a Lead Data Scientist, you will lead the design, development, validation, and operationalization of machine learning and advanced analytics solutions that power intelligent products and business capabilities. This role combines strong hands\-on expertise in model development with practical experience in MLOps, deployment, monitoring, and lifecycle management. You will work closely with product managers, domain experts, engineers, architects, and platform teams to turn business problems into scalable, production\-grade ML solutions. In addition to building models, you will guide feature engineering strategies, experimentation approaches, validation standards, and production\-readiness practices to ensure models are reliable, explainable, and maintainable in real\-world environments. This role is ideal for someone who is equally comfortable developing models, operationalizing them in production, and mentoring others to raise the maturity of data science and ML engineering practices across the team.. Key Responsibilities * Lead the design, development, evaluation, and deployment of machine learning models for predictive, classification, recommendation, anomaly detection, forecasting, and optimization use cases * Translate business and product requirements into well\-defined analytical approaches, model strategies, feature sets, evaluation methods, and deployment plans * Build robust and reusable pipelines for data preparation, feature engineering, model training, validation, hyperparameter tuning, and model packaging * Develop and operationalize production\-grade ML solutions with strong focus on reproducibility, maintainability, scalability, and measurable business impact * Partner with data engineers and software engineers to integrate models into applications, APIs, workflows, and downstream business systems * Design and implement MLOps practices including experiment tracking, model versioning, automated deployment, CI/CD for ML, monitoring, drift detection, retraining strategies, and rollback readiness * Establish model performance baselines and monitor production behavior for accuracy, drift, latency, stability, explainability, and business outcomes * Contribute to best practices for model governance, feature lineage, documentation, testing, interpretability, and responsible AI * Guide technical decisions on ML solution design, operationalization patterns, and production support expectations * Mentor other data scientists and ML engineers on modeling rigor, experimentation practices, and production\-readiness standards * Contribute reusable assets such as feature templates, modeling utilities, evaluation frameworks, deployment patterns, and internal accelerators * Work with tools and platforms such as Azure Machine Learning, Databricks, MLflow, Azure DevOps, GitHub, Docker, Kubernetes, Azure Functions, Azure Container Apps, Azure Monitor, and Application Insights (or equivalent platforms and tools) Preferred Qualifications * Experience leading complex ML initiatives involving multiple models, cross\-functional teams, and production operationalization * Experience with time\-series forecasting, optimization, recommender systems, anomaly detection, NLP, or domain\-specific applied AI use cases * Familiarity with LLM\-assisted analytics, embeddings, retrieval\-enhanced ML workflows, or hybrid ML \+ GenAI solution patterns * Experience integrating ML solutions into enterprise applications, APIs, business workflows, and digital products * Experience with feature stores, explainability frameworks, responsible AI toolkits, and model governance controls * Familiarity with Azure OpenAI, Azure AI Studio, Azure AI Search, or equivalent platforms where ML and GenAI capabilities coexist * Experience contributing reusable frameworks, MLOps standards, internal accelerators, or shared data science utilities * Working knowledge of distributed training, large\-scale data processing, and performance optimization in production environments * Experience with advanced MLOps and platform tooling such as MLflow, Kubeflow, Azure ML, TensorBoard/ TensorFlow Extended, or equivalent ecosystem tools * Experience operating in a build\-own\-operate product environment with strong expectations around reliability, observability, supportability, and continuous improvement * Ability to influence architectural and platform decisions for ML\-enabled products while remaining hands\-on in model development and operationalization Work Location: Bengaluru East, Karnataka, India Availability: Full time
Job Title: Staff Machine Learning Engineer Company: Warner Bros. Discovery Job Category: Machine Learning Roles & Responsibilities: Roles \& Responsibilities * Own the architecture and roadmap of the model serving runtime, supporting multiple ML frameworks and inference engines behind one control plane * Lead large\-scale migrations and rollouts of production models onto the platform with zero viewer\-facing regressions * Build and maintain serving backends, model configurations and batching strategies that meet strict tail\-latency targets at high request volume * Design autoscaling, capacity management and multi\-region resilience for latency\[1]critical serving across Max, Discovery\+ and other WBD offerings * Drive observability, cost optimization and performance tuning across the serving fleet, including hardware selection, GPU and CPU utilization, and model optimization * Define the contract between model training and serving so a validated model artifact deploys to production through standard, automated paths * Establish per\-model SLOs with model owners and build the telemetry that proves them * Collaborate with applied scientists, partner engineering teams and the core infrastructure team as the platform onboards new models, runtimes and markets * Author, test, review and optimize production\-level code in Python while executing best practices in version control, CI/CD and code integration * Take part in the platform on\-call rotation and lead incident reviews that result in design changes, not just fixes * Contribute design documents and technical documentation to support architecture decisions, knowledge transfer and sharing * Mentor engineers, raise the bar in design and code reviews, and represent the platform in cross\-team architecture decisions * 9\+ years of industry experience * 5\+ years of experience building or operating production ML infrastructure or comparable low\-latency, large\-scale distributed systems with a large customer base * Hands\-on experience running model inference in production at scale * Strong Kubernetes fundamentals and experience running GPU and CPU workloads on it * Proven performance engineering skills: profiling, tail\-latency analysis, batching and concurrency under load * 7\+ years of programming experience in Python, plus working fluency in a systems language such as C\+\+, Go or Rust * Good practical knowledge of the modern machine learning lifecycle, from training artifacts through deployment, rollout and monitoring * Strong architectural and design skills, with a track record of leading multi\-quarter technical initiatives across teams * Operational maturity: experience owning a tier\-1 service, including on\-call * Experience with one of the cloud platforms AWS/GCP/Azure, Docker and Kubernetes, and CI/CD tools like GitHub Actions, Jenkins etc. * Excellent written and verbal communication skills; comfortable contributing to technical documentation and on\-call support * Ability to technically collaborate with partners across time zones 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: Karnataka, India Availability: Full time
Job Title: Applied Scientist II, International Machine Learning Company: Amazon Job Category: Machine Learning Roles & Responsibilities: We are developing state\-of\-the\-art machine learning solutions to accelerate the Amazon India growth story. Amazon India is an exciting place to be at for a machine learning practitioner. We have the eagerness of a fresh startup to absorb machine learning solutions, and the scale of a mature firm to help support their development at the same time. As part of the India Machine Learning team, you will get to work alongside brilliant minds motivated to solve real\-world machine learning problems that make a difference to millions of our customers. We encourage thought leadership and blue ocean thinking in ML. Key job responsibilities Design, develop, evaluate and deploy, innovative and highly scalable ML models Work closely with software engineering teams to drive real\-time model implementations Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model maintenance Work proactively with engineering teams and product managers to evangelize new algorithms and drive the implementation of large\-scale complex ML models in production Leading projects and mentoring other scientists, engineers in the use of ML techniques About The Team International Machine Learning Team is responsible for building novel ML solutions that attack India first (and other Emerging Markets across MENA and LatAm) problems and impact the bottom\-line and top\-line of India business. Learn more about our team from https://www.amazon.science/working\-at\-amazon/how\-rajeev\-rastogis\-machine\-learning\-team\-in\-india\-develops\-innovations\-for\-customers\-worldwide Work Location: Bengaluru, Karnataka, India Availability: Full time
Job Title: Software Engineer Company: Cisco Job Category: Machine Learning Roles & Responsibilities: * Build AI applications and agents: Develop and evaluate industrial applications and agentic workflows using LLMs, SLMs, machine learning, computer vision, RAG, MCP, and tool calling. * Apply AI to industrial networking and security: Develop capabilities for smarter network operations, troubleshooting, observability, anomaly detection, and threat detection. * Develop Edge AI: Fine\-tune, optimise, and deploy ML models and SLMs on edge platforms, balancing model quality, memory, compute, and latency for reliable on\-device inference. * Practice AI\-first product development: Use coding agents and agentic workflows across design, implementation, debugging, testing, and review. Collaborate with domain and AI engineers to deliver reliable software, validating correctness, performance, and security. You approach engineering with an AI\-native mindset, use coding agents and automation thoughtfully, and take responsibility for correctness, security, and quality. You are curious about industrial systems and eager to learn the networking and platform context your work requires. If you are the target of a recruiting scam, consider filing a report with your local law enforcement authorities. Cisco bears no responsibility, and cannot be held liable, for any claims, damages, expenses, or other inconvenience resulting from or in any way connected to recruiting scams. Work Location: Bengaluru, Karnataka, India Availability: Full time
