Job Title: Sr Engineer - AI COE Company: Tata Communications Job Category: Machine Learning Roles & Responsibilities: Role Summary We are hiring a Sr. Engineer (2\+ years) for the AI CoE to build and deploy Generative AI, RAG, Agentic AI, and Machine Learning solutions. This role combines LLM\-driven applications with strong ML fundamentals, supporting scalable and monetizable AI products for telecom and enterprise use cases. Key Responsibilities * Build and deploy LLM\-based applications, RAG, and Agentic RAG systems * Develop multi\-agent workflows using tools like LangChain, LlamaIndex, LangGraph, Azure, and AWS Bedrock * Integrate MCP tools, APIs, and function\-calling into AI systems * Design prompting strategies, embeddings, and vector search pipelines using Milvus / FAISS / Pinecone * Implement structured output generation for LLM responses (JSON/schema\-driven outputs) * Apply machine learning techniques (classification, clustering, predictive modeling) for telecom and enterprise use cases * Perform data preprocessing, feature engineering, and model evaluation * Optimize solutions for performance, scalability, cost, and latency * Develop backend APIs using FastAPI for serving AI/ML models * Containerize applications using Docker for scalable deployment * Implement monitoring, logging, and observability using Grafana and ELK stack * Enable LLM traceability and observability using Langfuse etc. * Collaborate with product and engineering teams to deliver production\-grade AI solutions Additional Note Role involves hands\-on Python coding and system design assessments, covering machine learning fundamentals, model building, RAG, LLMs, agent\-based applications, LangGraph workflows , API development, and production deployment considerations (Docker, monitoring, traceability). Work Location: Bengaluru, Karnataka, 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: Regional Research Economist, Economic Research Company: Anthropic Job Category: Machine Learning Roles & Responsibilities: Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role ------------------ As a Regional Research Economist at Anthropic, you will collaborate with governments, academia, industry, and civil society in your region to measure and understand AI’s effects on the economy and explore research\-driven policy interventions. You will contribute to the development of the Anthropic Economic Index and its extension to generate regionally relevant insights, establish new methodologies to measure the usage, diffusion, and impact of AI throughout the economy, and work to broaden access to and usage of the insights generated by the Index. You will use frontier methods in econometrics, machine learning, and structural estimation. Such rigor will drive impact, shaping both policy discussions externally and informing Anthropic’s internal business and product decisions. For this role, we’re looking for candidates who can combine rigorous economic analysis with novel measurement approaches to understand AI’s transformative effects on the economy. The ideal candidate will be comfortable working at the intersection of empirical economics, technological change, and policy impact. Key responsibilities ------------------------ * Build and maintain relationships with academic institutions, policy think tanks, and other research partners as the primary point of contact for these organizations on economic impact work in your region * Advance research collaborations that answer country\- or regional\-specific economic impact questions * Translate research insights into actionable recommendations for policy discussions * Make fundamental contributions to the development and expansion of the Anthropic Economic Index, including country\- and regional\-specific analysis * Design and collaborate on empirical research on AI’s economic effects with governments, academia, industry, and civil society in your region * Develop new methodological approaches, in collaboration with partners in your region, for studying AI’s impact on labor markets and the future of work; productivity and task transformation; economic inequality and displacement; industry\-specific disruption and adaptation; and aggregate economic trajectories (GDP, productivity, unemployment) under varying AI\-adoption scenarios * Work cross\-functionally with other technical teams to improve our measurement infrastructure and data collection * Amplify external engagement through research publications, policy briefs, and presentations to diverse stakeholders Location\-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. Work Location: 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: Applied Scientist II, Advertising Trust Company: Amazon Science Job Category: Machine Learning Roles & Responsibilities: This is a hands\-on science role with real ownership. You will work across large multilingual datasets, modern ML and large language model techniques, and tight engineering constraints, partnering closely with other scientists, engineers, and product teams to turn research into measurable customer impact. Key job responsibilities Work Location: Bengaluru, Karnataka, 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: AI/ML Company: Infosys Job Category: Machine Learning Roles & Responsibilities: Job Description: -------------------- Key Responsibilities: ------------------------- * Design develop train test and deploy Machine Learning models for business use cases * Build and optimize predictive classification recommendation and forecasting models * Develop and implement NLP LLM and Generative AI solutions * Perform data collection cleaning feature engineering and exploratory data analysis * Fine tune and optimize pre trained models for domain specific applications * Develop APIs and microservices to expose AI ML models * Implement MLOps practices for model deployment monitoring versioning and retraining * Work with large datasets and distributed processing frameworks * Collaborate with cross functional teams to understand business requirements and translate them into AI solutions * Monitor model performance accuracy and drift in production environments * Create technical documentation and best practices for AI ML implementations * Python SQL Data Structures Algorithms * Machine Learning Deep Learning TensorFlow PyTorch Scikit Learn * Generative AI LLMs LangChain RAG Prompt Engineering * AWS Azure GCP Docker Kubernetes MLOps CI CD * NLP Vector Databases FAISS Pinecone ChromaDB Pandas NumPy API Development Work Location: Karnataka, India Availability: Full time
Job Title: GenAI Developer Company: Infosys Job Category: Machine Learning Roles & Responsibilities: Design and implement advanced Generative AI models to solve complex problems. \- Collaborate with cross\-functional teams to integrate AI solutions into existing systems. \- Conduct research and stay updated with the latest advancements in NLP and AI technologies. \- Develop scalable and efficient AI algorithms to enhance product offerings. \- Mentor junior team members and share knowledge to foster a culture of learning. Good to have skills: Machine Learning, Data Analysis, Deep Learning, Python Programming, Cloud Computing Work Location: Bengaluru East, Karnataka, India Availability: Full time
Job Title: Sr Engineer - AI COE Company: Tata Communications Job Category: Machine Learning Roles & Responsibilities: Role Summary: We are hiring a Sr. Engineer (2\+ years) for the AI CoE to build and deploy Generative AI, RAG, Agentic AI, Machine Learning \& Data Engineering solutions. This role combines LLM\-driven applications with strong ML fundamentals, supporting scalable and monetizable AI products for telecom and enterprise use cases. Key Responsibilities: * Build and deploy LLM\-based applications, RAG, and Agentic RAG systems * Build optimized data pipeline to support AI applications * Develop multi\-agent workflows using tools like LangChain, LlamaIndex, LangGraph , Azure, and AWS Bedrock * Integrate MCP tools, APIs, and function\-calling into AI systems * Design prompting strategies, embeddings, and vector search pipelines using Milvus / FAISS / Pinecone * Implement structured output generation for LLM responses (JSON/schema\-driven outputs) * Apply machine learning techniques (classification, clustering, predictive modeling) for telecom and enterprise use cases * Perform data preprocessing, feature engineering, and model evaluation * Optimize solutions for performance, scalability, cost, and latency * Develop backend APIs using FastAPI for serving AI/ML models * Containerize applications using Docker for scalable deployment * Implement monitoring, logging, and observability using Grafana and ELK stack * Enable LLM traceability and observability using Langfuse etc. * Collaborate with product and engineering teams to deliver production\-grade AI solutions Required Skills: * 2\+ years of experience in Data Engineering / AI / Machine Learning /Gen AI * Excellent proficiency in Python and working knowledge of SQL ( PostgreSQL preferred ) * Hands on Data Engineering experience with big data tools and technology. Role involves hands\-on Python coding and system design assessments, covering machine learning fundamentals, model building, RAG, LLMs, agent\-based applications, LangGraph workflows , API development, and production deployment considerations (Docker, monitoring, traceability). Work Location: Karnataka, India Availability: Full time
Job Title: Technical Program Manager, Product Ops Digitization Company: Google Job Category: Machine Learning Roles & Responsibilities: * Experience in high\-volume factory operations, NPI, process management, and overseeing contract manufacturers. * Experience with data analytics, data visualization, architecting complex business intelligence solutions and data pipelines using SQL and Python. * Proven ability to present complex data analysis, yield trends, and proactive actionable alerts to executive leadership and external contract manufacturing partners. * Solid foundation in applied statistics and quantitative analysis, alongside an understanding of basic machine learning concepts to apply predictive models to manufacturing operations. * Excellent technical program management skills, with a demonstrated ability to solve complex problems independently and automate manual workflows for efficiency gains. A problem isn’t truly solved until it’s solved for all. That’s why Googlers build products that help create opportunities for everyone, whether down the street or across the globe. As a Technical Program Manager at Google, you’ll use your technical expertise to lead complex, multi\-disciplinary projects from start to finish. You’ll work with stakeholders to plan requirements, identify risks, manage project schedules, and communicate clearly with cross\-functional partners across the company. You're equally comfortable explaining your team's analyses and recommendations to executives as you are discussing the technical tradeoffs in product development with engineers. Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise\-grade solutions that leverage Google’s cutting\-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.Responsibilities -------------------- * Identify opportunities to automate manual processes. Collaborate with relevant teams to develop tools and scripts that streamline processes and improve efficiency. Design, develop and run systems that automate Alphabet’s supply chain and manufacturing operations. * Effectively translate complex technical and engineering issues into clear, concise summaries that are easily understood by management and cross\-functional teams. Facilitate communication between different teams and ensure tight coordination. * Prepare executive\-level presentations and reports that distill complex data into actionable insights. * Provide comprehensive program management support, including ongoing development of processes, templates, escalation procedures, and reporting mechanisms. Ensure smooth execution of projects. * Demonstrate proficiency in AI/ML concepts. Use AI to automate end\-to\-end processes, streamline coordination, and accelerate the execution of your programs Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form. Work Location: Karnataka, India Availability: Full time
