Job Title: Data Scientist Company: Mahindra & Mahindra Ltd Job Category: Machine Learning Roles & Responsibilities: Responsibilities \& Key Deliverables ---------------------------------------- Role Summary We are looking for a hands\-on, algorithm\-strong ML/DL leader who can own and drive high\-impact AI initiatives in Product Development (PD)—from data strategy to model development, validation, and deployment. The role demands deep expertise in core machine learning and deep learning fundamentals, and strong experience with time\-series sensor data and signal processing (preferred), to build robust, production\-grade models that deliver measurable reductions in engineering cycle time and automation of PD workflows. This is not a reporting\-only analytics role—you will lead initiative delivery, mentor engineers, and build scalable ML systems end\-to\-end. You will contribute to and lead high\-impact AI initiatives that transform the automotive product development process and materially accelerate program timelines. You will work on complex, challenging, and highly rewarding problems that redefine the way vehicle platforms are engineered, simulated, and tested—enabling faster decisions, improved quality, and scalable AI\-driven execution across PD. Key Responsibilities • Design and implement ML/DL architectures for structured and time\-series data: gradient boosting, deep sequence models, representation learning, multi\-modal learning, uncertainty estimation, and robust generalization. • Build and maintain end\-to\-end ML pipelines in Python. • Enable monitoring, retraining, and governance for model performance over time. • Demonstrated ability to own outcomes, lead projects independently, and ship production\-grade solutions. Work Location: Maharashtra, India Availability: Full time

Job Title: AI-ML Researcher Company: AkzoNobel Job Category: Machine Learning Roles & Responsibilities: Job Purpose The Technology Integration Team develops and productizes reusable Color Technology Components that power AkzoNobel’s internal applications and external customer\-facing tools, with focus areas in Colorimetric Engines/Building Blocks, Color Visualization, and AI/ML\-enabled color services. The AI/ML Researcher owns the delivery of applied Machine Learning and statistical solutions for prioritized color and coatings use cases (e.g., formulation optimisation, pigment/raw material screening, quality prediction, and image\-based inspection). The role translates business and R\&D questions into well\-structured datasets, validated ML models, and clear insights, and partners with engineering and product stakeholders to ensure solutions are deployment\-ready, monitored, documented and usable in products and processes. Unlike generalist Researcher roles, this position brings dedicated applied ML/data science capability to the team, owning the end\-to\-end ML lifecycle from problem framing through deployment\-ready model delivery. Key Accountabilities * Use case shaping \& stakeholder partnering * Engage with R\&D, lab teams, manufacturing and product/application stakeholders to translate needs into well\-defined ML problems, required inputs/outputs, constraints, and measurable success criteria. * Lead or co\-lead end\-to\-end delivery for assigned use cases from discovery and scoping through experimentation, validation, and implementation readiness. * Communicate trade\-offs (accuracy vs. explainability, latency, cost, robustness) and guide stakeholders toward fit\-for\-purpose solutions. * Data preparation, analysis \& modelling * Acquire, clean, integrate, and analyze data from R\&D/lab systems, manufacturing sources, and internal datasets; assess data quality, bias, leakage risk, and suitability for modelling. * Develop, benchmark, and validate ML models (supervised/unsupervised) including baseline creation, feature engineering, model selection, hyperparameter tuning, and robustness checks. * Domain application (color/coatings) * Collaborate with color formulators, researchers, and lab teams to ensure modelling aligns with domain realities (measurement variability, protocols, material constraints). * Define and drive dataset design/generation activities (e.g., DoE support, sampling strategy, labeling guidance, protocol awareness) to improve training data quality and coverage. * Apply practical understanding of relevant color data types (spectral/Lab\/ΔE and variability) when designing targets, features, and evaluation strategies (as applicable). * Computer vision (where relevant) * Deliver image\-based modelling tasks (e.g., defect detection, surface uniformity, pigment recognition) using classical CV and deep learning methods; define evaluation metrics and acceptance criteria aligned to operational deployment. * Ensure peer review and alignment with Senior Researchers/architects for high impact use cases and model choices that may affect product/process behavior. * Industrialization \& production readiness * Drive implementation readiness of assigned models: reproducible training/inference code, model artifacts, data dependencies, parameterization, testing approach, and clear runbooks. * Contribute to MLOps practices as defined by the team: version control, experiment tracking, model registry inputs, monitoring requirements, alert thresholds, and retraining triggers. * Partner with application/software teams to integrate model outputs into components/services (APIs, batch pipelines, or embedded usage) and support post\-deployment stabilization. At AkzoNobel we are highly committed to ensuring an inclusive and respectful workplace where all employees can be their best self. We strive to embrace diversity in a context of tolerance. Our talent acquisition process plays an integral part in this journey, as setting the foundations for a diverse environment. For this reason we train and educate on the implications of our Unconscious Bias in order for our TA and hiring managers to be mindful of them and take corrective actions when applicable. In our organization, all qualified applicants receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age or disability. Work Location: Bengaluru East, Karnataka, India Availability: Full time

Job Title: Data Architect AVP Company: HSBC Job Category: Machine Learning Roles & Responsibilities: If you’re looking for a career that will help you stand out, join HSBC and fulfil your potential. Whether you want a career that could take you to the top, or simply take you in an exciting new direction, HSBC offers opportunities, support and rewards that will take you further. In this role, you will be: * In conjunction with the Chief Data and Analytics Officer, refine and uphold the Data Strategy. The Data Architecture function is responsible for ensuring that the implementation of the services aligns to the original strategy and supporting implementation change teams. * Support the Data Analytics capability which uses Cloud and Data Science methods and technologies to provide business insights and contribute to the design and ensure adoption in Asset Management of HSBC Group Data Management Standards * Publish data assets and data quality rules and requirements to the Group Data Dictionary, Collibra (or) similar data governance tools. * Manage and maintain Asset Management data models (conceptual and logical predominantly but also physical for Cloud adoption of core data services) * Enable data team by providing (Google Cloud Platform) GCP\-based architectural guidance, driving design decisions, and ensuring consistent adoption of data models, standards, and frameworks. * Exposure to (Artificial intelligence/machine learning)AI/ML architecture, including model lifecycle management, MLOps concepts, and experience working with GCP’s AI ecosystem. (Vertex AI, Bigquery ML). * Preferred exposure to programming languages (such as Python), with the ability to build prototypes and proof\-of\-concept (POC) solutions for data and AI initiatives. * Work with project teams to facilitate the safe sharing of data cross border and demonstrate a high level of accountability and ownership throughout the lifecycle of data solutions * 5 to 12 years’ experience in Investment banking or banking domain with any post\-graduation * Translate complex technical concepts into clear business terms for non\-technical stakeholders, enabling data\-driven decisions. * Able to define data standards, patterns and architectural principles to ensure consistency, scalability, reusability and alignment across all data initiatives. * Asset Management domain knowledge is beneficial and will support effective understanding of business processes and operational needs * Good to have product\-led thinking, with the ability to model, design, and build data products for future\-ready analytics and AI initiatives. * Good team player who can work with global and local functional team members in different time zones and who can foster and maintain good relationships. HSBC is an equal opportunity employer committed to building a culture where all employees are valued, respected and opinions count. We take pride in providing a workplace that fosters continuous professional development, flexible working and, opportunities to grow within an inclusive and diverse environment. We encourage applications from all suitably qualified persons irrespective of, but not limited to, their gender or genetic information, sexual orientation, ethnicity, religion, social status, medical care leave requirements, political affiliation, people with disabilities, color, national origin, veteran status, etc., We consider all applications based on merit and suitability to the role.” Work Location: Karnataka, India Availability: Full time

Job Title: Data Scientist Company: Cummins Inc. Job Category: Machine Learning Roles & Responsibilities: Key Responsibilities: Leverages data science methodology to solve business problems. Creates individual algorithms using statistical methodologies through the use of statistical programming languages and tools. Partners with domain experts to verify model capabilities. Implements statistical techniques to clean, prepare and profile the data prior to deeper analysis. Clearly articulates results, methodologies and learnings to stakeholder and peer group. Continuous development and advancement of the team through knowledge sharing and collaboration. Communicates effectively \- Developing and delivering multi\-mode communications that convey a clear understanding of the unique needs of different audiences. Manages complexity \- Making sense of complex, high quantity, and sometimes contradictory information to effectively solve problems. Predictive Modeling \- Develops analytical or machine learning models by using appropriate variable transformations, feature selection strategies, imputation strategies, class rebalancing, resampling strategies and quality control measures to generate predictive insights used in solving business questions. Statistical Modeling \- Develops descriptive and explanatory statistical models, and simulations for regression, classification, outlier detection, anomaly detection, time series forecasting using knowledge of foundational statistics such as null hypotheses significance tests, regression models, generalized linear modeling, time series analysis, rank statistics, probability distribution fitting survival analysis, etc. to validate hypotheses for any given statistical or business question. Problem Solving \- Solves problems and may mentor others on effective problem solving by using a systematic analysis process by leveraging industry standard methodologies to create problem traceability and protect the customer; determines the assignable cause; implements robust, data\-based solutions; identifies the systemic root causes and ensures actions to prevent problem reoccurrence are implemented. Ability to manage complexity and prioritize high\-value opportunities. Software Development: Knowledge of version control, testing frameworks, CI/CD, and secure development practices. Manages Complexity Role Category On\-site with Flexibility Work Location: Indi, India Availability: Full time

Job Title: Software Engineer - Data Quality Company: Truveta Job Category: Machine Learning Roles & Responsibilities: Join the founding team of the Truveta India Development Center and play a pivotal role in shaping its future. As one of the early members, you will help build and scale a high\-impact organization while contributing to the products and platforms that advance healthcare through data and AI. This is an unusual chance to influence both the technical direction and the culture of a growing global engineering hub. Patients, doctors, and medical researchers deserve to benefit from the large\-scale technological innovation and digital intelligence that have driven progress in other industries. In this position you will build online services, automation, and tooling that monitor Truveta's data and make sure it continues to meet our high\-quality standards. The work calls for creative problem solving and a strong appetite for applying AI and machine learning to anomaly detection, supported by statistical methods, to monitor and reason over big data at scale. What you will do In this role you will: * Build performant AI\-based anomaly detection and monitoring systems, using machine learning and supporting statistical methods to analyze big data at scale. * Design, implement, test, deploy, operate, and tune the online services, automation, and tooling that monitor Truveta's data, contributing hands\-on to every stage of the software development lifecycle. * Detect and characterize data\-quality issues such as missing or late feeds, volume and distribution shifts, schema and contract drift, duplication, and implausible clinical values. * Develop and evaluate detection approaches, from statistical baselines and time\-series methods through machine\-learning models, and measure them on precision, recall, and alert usefulness rather than accuracy alone. * Turn detection output into signals people can act on: alerts with root\-cause context, data\-quality metrics, and dashboards that engineering and clinical teams trust. * Work with data\-processing engineers to build quality checks into pipelines so that defects are caught where they are introduced. * Collaborate with cross\-functional teams including product managers, clinical informaticists, architects, and other engineers to define what quality means for each data domain. * Take part in design reviews, code reviews, and the on\-call rotation for the services you own. * Experience developing and evaluating AI or machine\-learning approaches for anomaly detection, with supporting knowledge of statistical methods, time\-series analysis, or data\-quality monitoring. * Experience working as part of distributed teams, particularly across India and the United States. * Experience processing large datasets with Spark, Databricks, or comparable distributed frameworks, and strong SQL. * Experience running services on Microsoft Azure. * Familiarity with data\-quality and observability tooling such as Great Expectations, Deequ, Soda, or equivalent in\-house frameworks. * Experience operating machine\-learning models in production, including drift monitoring and retraining. * Exposure to healthcare, clinical, or other regulated data. Work Location: Telangana, India Availability: Full time

Job Title: Machine Learning Intern Company: Enterpret Job Category: Machine Learning Roles & Responsibilities: Enterpret is redefining how businesses understand and act on customer feedback. We are building an AI\-native platform that centralises feedback from every source surveys, reviews, support tickets, communities and turns it into clear, actionable insights that drive business growth. We are trusted by some of the world’s most customer\-obsessed companies like Canva, Descript, Notion, Perplexity and many more, and backed by leading investors like Kleiner Perkins, Canaan Partners, and Peak XV Partners. Our mission: to unlock the voice of the customer for every product team on the planet. * Build and prototype LLM\-backed features alongside senior engineers — retrieval pipelines, agents, evaluation harnesses, or hybrid patterns — and ship a meaningful slice of one into production by the end of the internship. * Contribute to eval rubrics, test plans, and quality dashboards that make AI feature quality measurable, and run evals on shipped systems. * Write clean, testable Python in our production stack, add tests that catch regressions, and help monitor and harden systems already in production. * Debug failures across data, infra, model, and prompt logic with your mentor, and write up what you learn so the team learns with you. * Collaborate with engineers, product, and the AI team — joining design reviews, shipping PRs, and participating in design decisions on features you contribute to. * Continuously raise the bar on your own craft: ask sharp questions in code reviews, read the systems before you change them, and push for quality without being asked. * Demonstrated AI/ML project depth — coursework, research, open\-source, hackathons, or prior internships where you've built something non\-trivial with LLMs and evaluated it rigorously. * At least one substantial project where you owned a system end\-to\-end — designed it, built it, and dealt with what broke. Tenure of effort matters more than tenure of employment. * Solid engineering skills in Python: you write clean, testable code, debug at system boundaries, and are comfortable in production\-style stacks. * Working knowledge of modern LLMs — prompting, fine\-tuning, retrieval, agents, or evaluation. You've gone deeper than a tutorial on at least one of these. * A systems mindset: you think in interfaces, data contracts, failure modes, and rollout plans — not just model tweaks. * A track record of collaborating and learning in the open — asking sharp questions, giving and taking feedback, and pushing for quality without being asked. * Available to work full\-time onsite in Bengaluru for the internship duration, with intent to convert to a full\-time role. ### What You’ll Gain ? * Mentorship from engineers who have scaled AI\-native systems. * Exposure to cutting\-edge tech * Understanding of real\-world product development in a high\-growth AI\-driven startup. * Competitive internship stipend. * Learning \& development resources in AI technologies. Work Location: Bengaluru, India Availability: Full time

Job Title: Software Engineer, Security, Privacy, Detection Company: Google Job Category: Machine Learning Roles & Responsibilities: Google's software engineers develop the next\-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large\-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast\-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full\-stack as we continue to push technology forward. Responsibilities -------------------- Work Location: Telangana, India Availability: Full time

Job Title: Machine Learning Engineer III Company: CommerceIQ Job Category: Machine Learning Roles & Responsibilities: At CommerceIQ, we help consumer brands accelerate their retail ecommerce market share growth and profitability through machine learning algorithms. We are building the world's most complete and sophisticated Retail Ecommerce Management Platform, which connects and intelligently automates the management of retail ecommerce channels like Amazon, Walmart, and Instacart, across the entire ecommerce operational chain of retail media management, sales operations, supply chain, and digital self analytics. As an ML Engineer in the team, you will work closely with Data Science, Engineering, Platform, Product and Operations teams to build state\-of\- the\-art ML based solutions for B2B SaaS products. This will entail applying advanced ML algorithms at scale for core products and developing robust end to end production pipelines which includes Human\-in\-the\-Loop component to boost the quality. The ideal candidate will have a strong background in machine learning model development, deploying large scale, high throughput machine learning pipelines to production, experience with developing and managing frameworks for machine learning platforms, which they can utilise to manage and improve our company's AI/ML initiatives. * Contribute to development of multiple AI driven end to end pipelines that allows for deployment and scalability of machine learning models * Build an end\-to\-end machine learning platform, covering all lifecycle stages of a model, to ease model development and deployment * Build tools and capabilities that help with data ingestion to feature engineering, data management and organisation * Deploy cutting edge algorithms like LLMs etc. on GPUs along with distributed computing for scalability * Contribute to tools and capabilities for model management and model performance monitoring * Implement the best engineering practices for scaling ML\-powered features, with a goal to enable the fast iteration of and efficient experimentation with novel features * Champion and own the ML infrastructure roadmap, in collaboration with Data Science and other platform teams We have multiple brands, which are among the biggest brands operating on Amazon, as our customers. You will be responsible for working with their data and developing models and algorithms to drive lift in tune of hundreds of thousands of dollars. * Opportunity to work on cutting edge technologies in text and images data like LLMs, OCR, transformer based embeddings models. * Deploy code using the most advanced tech stack like AWS, GCP etc. * You will own projects end to end i.e., from exploration to final production * You will be empowered to make decisions. It implies more responsibilities but high learning * Immense opportunities to learn and develop ML based SaaS products for brands and get company\-wide recognition * Forget endless meetings. Get things done and start making an impact from day 1 * Work hard, have amazing fun, create history, build the future of eCommerce * Start\-up environment with a strong culture and values to accelerate your career Work Location: Bengaluru, India Availability: Full time

Job Title: Engineer, Senior Staff Company: Qualcomm Job Category: Machine Learning Roles & Responsibilities: We are seeking a highly skilled and motivated Language Model Engineer to join our team. The primary role of the engineer will be to train Large Language Models (LLMs) from scratch and fine\-tune existing LLMs on various datasets using state\-of\-the\-art techniques. Responsibilities Model architecture optimizations : optimize latest LLM and GenAI model architectures for NPUs, which involves reimplementing basic building blocks of models for NPUs Model Training and Fine\-tuning: Fine\-tune pre\-trained models on specific tasks or datasets to improve performance. Implement state\-of\-the\-art LLM training techniques such as Reinforcement Learning from Human Feedback (RLHF), ZeRO (Zero Redundancy Optimizer), Speculative Sampling, and other speculative techniques. Data Management: Handle large datasets effectively. Ensure data quality and integrity. Implement data cleaning and preprocessing techniques. Hands\-on with EDA is a plus. Research and Development: Stay up to date with the latest research in NLP and LLMs. Implement state\-of\-the\-art techniques and contribute to research efforts. Infrastructure development : For coming up with new optimization techniques to minimize ONNX memory footprint, export time optimizations. Applicants : Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e\-mail disability\-accomodations@qualcomm.com or call Qualcomm's toll\-free number found here. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries). If you would like more information about this role, please contact Qualcomm Careers. Work Location: Bengaluru, Karnataka, India Availability: Full time

Job Title: HR GHRSS HRIT Hyd 171336 Company: ADP Job Category: Machine Learning Roles & Responsibilities: Job Summary: Seeking an experienced AWS AI Data Engineer to design, build, and optimize scalable data and AI/ML solutions on AWS Cloud. The ideal candidate should possess strong expertise in modern data engineering, cloud\-native architecture, machine learning data pipelines, and Generative AI solutions. The role involves developing robust data platforms, enabling AI workloads, and collaborating with data scientists, ML engineers, and business stakeholders to deliver impactful analytics and AI\-driven solutions. Key Responsibilities: Design, develop data ingestion solutions from APIs, databases, and maintain scalable ETL/ELT pipelines on AWS. Design, develop, and deploy Generative AI applications using Amazon Bedrock, SageMaker, and foundation models. Build and implement Retrieval\-Augmented Generation (RAG) solutions leveraging vector databases and enterprise knowledge repositories. Enable AI/ML and Generative AI workloads through robust data pipelines. Integrate Large Language Models (LLMs) with enterprise systems, APIs, and business workflows. Design and optimize prompts, evaluate model performance, and improve response quality through prompt engineering techniques. Implement AI guardrails, content filtering, and responsible AI practices to ensure safe and compliant GenAI deployments. Monitor GenAI application performance, model usage, latency, and costs while ensuring scalability and reliability. Implement and ensure data quality, governance, security, scalability, and cost\-effective AWS data platforms. Collaborate with Data Scientists, ML Engineers, and business stakeholders. Develop conversational AI solutions, enterprise copilots, intelligent search, and knowledge\-management applications. Document technical solutions and support Agile delivery practices. \#\#LI\-DNI Required Skills Strong experience with AWS Services: S3, Glue, Lambda, Redshift, DynamoDB, IAM, Step Functions, API Gateway, EC2, ECS/EKS. Proficiency in Python, PySpark and SQL. Hands\-on experience with Amazon SageMaker and/or Amazon Bedrock, OpenSearch, Generative AI, RAG, Vector Databases, Prompt Engineering and LLM orchestration platforms. Experience implementing enterprise scale RAG architecture, embeddings, and vector databases (OpenSearch, pgvector, Pinecone, Chroma, etc.). Experience building and deploying scalable, secure, and production\-grade GenAI and Agentic AI applications on AWS. Strong understanding of Large Language Models (LLMs), Prompt Engineering, Retrieval\-Augmented Generation (RAG), AI Agents, Multi\-Agent Systems, and Conversational AI solutions. Experience building enterprise AI copilots, chatbots, document intelligence, or knowledge assistant solutions. Strong understanding of REST APIs, Microservices, CI/CD pipelines, Git, Docker, and cloud\-native development practices. Ability to work closely with business stakeholders and cross\-functional teams to identify use cases and deliver AI\-driven solutions. Excellent analytical, problem\-solving, and communication skills with a passion for innovation and emerging AI technologies. Preferred Skills: Experience with Data Lakes, ETL/ELT, Data Warehousing, and Data Modeling. Working experience with Terraform/CloudFormation, Git, CI/CD, and Docker. Exposure to LLMOps, model evaluation, prompt optimization, monitoring, governance, and Responsible AI practices. AWS Certifications (Developer Associate, Solutions Architect, Data Engineer, AI Practitioner) are a plus. Location: Hyderabad A little about ADP: We are a comprehensive global provider of cloud\-based human capital management (HCM) solutions that unite HR, payroll, talent, time, tax and benefits administration and a leader in business outsourcing services, analytics, and compliance expertise. We believe our people make all the difference in cultivating a down\-to\-earth culture that embraces our core values, welcomes ideas, encourages innovation, and values belonging. We've received recognition for our work by many esteemed organizations, learn more at ADP Awards and Recognition. Work Location: Telangana, India Availability: Full time