Job Title: Risk Analyst Company: EY Job Category: Machine Learning Roles & Responsibilities: Within Information Security we blend risk strategy, digital identity, cyber defense, application security and technology solutions as we consider the entire security lifecycle. You will join a team of hardworking, security\-focused individuals dedicated to supporting, protecting, and enabling the business through innovative, secure solutions that provide speed to market and business value. The Technology Assurance, Risk, and Policy (TARP) function within Information Security strives to create and promote a holistic Governance, Risk, and Compliance (GRC) program by creating a robust, resilient, and proactive governance framework, supported by a strategic risk management approach and stringent compliance structures. It aims to integrate and align its GRC initiatives in line with the global firm’s objectives and emerging threats within the cybersecurity landscape. Furthermore, the Policy, Risk, and Controls (PRC) Enablement \& Awareness team aims to manage the human element of risk through Human Risk Management, which involves security awareness, training, culture, and behavior management. Your key responsibilities The Global Behavioral Analytics \& AI Specialist sits within the Human Risk Management function and leverages artificial intelligence, data science, and behavioral science to measure, model, and manage human risk across EY. This role is the analytical and AI engine behind the security culture program—turning behavioral signals, engagement data, and risk indicators into insight that helps the organization understand why people behave the way they do and how to manage those behaviors at scale. Reporting to the Global Security Culture and Engagement Lead, this individual will partner across the awareness, learning, training, and simulation teams to build the metrics, models, and AI\-enabled capabilities that quantify culture and behavior change. Beyond measurement, they will act as an AI\-forward thought partner for the entire Human Risk Management team—identifying practical, responsible ways to apply AI both for intelligence and for service delivery. Key responsibilities include * Maintain and optimize a human risk measurement framework, defining the metrics and indicators that quantify security behaviors, culture, engagement, and human risk across the organization. * Leverage AI to analyze behavioral data, identify patterns and human risk indicators, and model or predict where risky behaviors are most likely to occur. * Work with stakeholders to consolidate data from across the Human Risk Management program into reporting that tells a clear, connected story. * Serve as the AI\-forward thought partner for the Human Risk Management team, identifying responsible and practical ways to apply AI for both intelligence (measurement, prediction, insight) and service offerings (e.g., AI\-powered solutions that reinforce secure behaviors). * Partner with the Security Culture and Engagement Lead to translate behavioral insight into targeted interventions, campaigns, and reinforcement strategies. * Develop executive\-ready reporting, visualizations, and recommendations that communicate human risk trends, program effectiveness, and return on investment to senior stakeholders. * Design and analyze surveys, assessments, experiments, and A/B tests to evaluate the impact of behavior change initiatives and continuously improve them. * Ensure that data and AI are used responsibly, ethically, and in line with EY privacy, data protection, security, and governance requirements. * Stay informed on developments in behavioral science, data science, AI, and human risk measurement, bringing new methods and innovation into the program. We’re looking for someone who can collaborate globally with different regions and cultures. Problem\-solves, thinks creatively, and has an open mind to new insights. Focus on customer service and building positive relationships with colleagues both across teams and globally. A highly motivated, diligent, and driven individual who seeks development and improvement opportunities and deliver quality services. As part of this role, you will work in a highly coordinated, globally diverse team with the opportunity and tools to grow, develop and drive your career forward. Here, you can combine global opportunity with flexible working. The EY benefits package goes above and beyond too, focusing on your physical, emotional, financial, and social well\-being. Your recruiter can talk to you about the benefits available in your country. Here’s a snapshot of what we offer: * Continuous learning: You will develop the mindset and skills to navigate whatever comes next. * Success as defined by you: We will provide the tools and flexibility, so you can make a significant impact, your way. * Transformative leadership: We will give you the insights, coaching and confidence to be the leader the world needs. * Diverse and inclusive culture: You will be accepted for who you are and empowered to use your voice to help others find theirs. Work Location: Bengaluru, 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: AI Apprentice Company: Siemens Healthineers Job Category: Machine Learning Roles & Responsibilities: We're looking for a curious, motivated AI Intern to join our team. This is a hands\-on role where you'll work alongside engineers and researchers on real AI/ML projects, from prototyping models to deploying them. You'll gain exposure to the full lifecycle of building AI products and have the opportunity to ship work that goes into production. * Assist in building, training, and evaluating machine learning and deep learning models * Work with large language models (LLMs) — prompt engineering, fine\-tuning, RAG pipelines, or agentic workflows * Clean, preprocess, and analyze datasets to support model development * Write clean, well\-documented Python code and contribute to internal tools and APIs * Help benchmark model performance and run experiments to improve accuracy and efficiency * Read recent AI research papers and share insights with the team * Collaborate with product, engineering, and design teams to integrate AI features into our products How we work: When you join Siemens Healthineers, you become one in a global team of scientists, clinicians, developers, researchers, professionals, and skilled specialists, who believe in each individual’s potential to contribute with diverse ideas. We are from different backgrounds, cultures, religions, political and/or sexual orientations, and work together, to fight the world’s most threatening diseases and enable access to care, united by one purpose: to pioneer breakthroughs in healthcare. For everyone. Everywhere. Sustainably. Work Location: Pune, 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: Data Scientist Company: Infosys Job Category: Machine Learning Roles & Responsibilities: * Experience: 4–6\+ years delivering end\-to\-end data science projects. * Education: Master’s or PhD in Data Science, Machine Learning, Statistics, Computer Science, Applied Mathematics, or related quantitative field (required from this level onward). * Core stack: Python, Spark, Git; ML frameworks; Databricks/MLflow (or equivalent); cloud basics. * Translate business needs into ML/AI problem statements and measurable success metrics. * Develop ML models and, where relevant, GenAI components (e.g., retrieval\-augmented generation, prompt pipelines) with clear evaluation criteria. * Run evaluation: offline metrics, error analysis, bias checks, and monitoring baselines; document decisions and assumptions. * Communicate results and limitations clearly to technical and non\-technical stakeholders; support adoption in workflows. * Python (pandas, numpy) \+ Git for reproducible development * Databricks (Notebooks, Workflows) for development and orchestration * ML flow (experiments, tracking, model registry) for lifecycle management * Azure (cloud services; where relevant Azure OpenAI and Azure AI Foundry for GenAI build/evaluation) * Databricks Mosaic AI (including Mosaic AI Model Serving) for GenAI delivery in the lakehouse * Databricks Vector Search for RAG retrieval patterns * Unity Catalog for governed data and model access (where applicable) * Lakehouse Monitoring / model monitoring for quality and drift (where applicable) Work Location: Hyderabad, Telangana, 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 Staff Engineer - Design Verification Power Management Company: SiFive Job Category: Machine Learning Roles & Responsibilities: As the pioneers who introduced RISC\-V to the world, SiFive is transforming the future of compute by bringing the limitless potential of RISC\-V to the highest performance and most data\-intensive applications in the world. SiFive’s unrivaled compute platforms are continuing to enable leading technology companies around the world to innovate, optimize and deliver the most advanced solutions of tomorrow across every market segment of chip design, including artificial intelligence, machine learning, automotive, data center, mobile, and consumer. With SiFive, the future of RISC\-V has no limits.* Our constant innovation and ongoing success is down to our amazing teams of incredibly talented people, who collaborate and support each other to come up with truly groundbreaking ideas and solutions. Solutions that will have a huge impact on people's lives; making the world a better place, one processor at a time. Job Description: Key Responsibilities: * Lead the verification and optimization of our diverse RISC\-V Low Power Profiles, including UPF. * Drive and achieve quality closure targets at both the CPU and block levels. * Collaborate closely with microarchitecture and RTL design teams to optimize complex Power flows. * Provide technical leadership and mentorship to junior team members to foster team growth and enrichment. * Actively participate in the test planning and execution phases for new architecture and design features. * 10\+ Years of experience in low power or power aware or power management * Experience with hands on UVM Test Bench development is must * Experience in core uArch is highly desirable. * Experience in leading effort and driving multiple projects * Experience with power simulation on vcs and upf. * Experience with script writing in Python, Perl or Tcl. * Experience with power impact at architecture, logic design, and circuit levels. * Excellent problem solving skill and ability to work in a dynamic and diverse environment. Work Location: Bengaluru, India Availability: Full time
Job Title: Machine Learning | Entry Level | Fresher Internship (Python, Scikit-learn, Model Evaluation) Company: MediNex Workforce Job Category: Machine Learning Roles & Responsibilities: What you will do Full\-time, Monday to Saturday or as assigned by your reporting manager, with daily check\-ins and a weekly review. Work Location: 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
