Top Machine Learning Jobs in Chennai

Develops and deploys AI and machine learning models and algorithms in production. Applies NLP, NLU, computer vision, deep learning, speech recognition, statistics, optimization, and probability theory to build practical AI solutions. Analyzes data, investigates complex problems, interprets results, and communicates analytics concepts to leadership and internal stakeholders. Requires an undergraduate degree or equivalent experience.

Sell SailPoint's IGA identity security SaaS to $5B+ enterprises by engaging C-level stakeholders, managing long sales cycles with POCs/RFPs, collaborating with GSIs and channel partners, developing account and opportunity plans, and meeting quota using Challenger methodology.

Leads AI transformation, governance, quality oversight, risk management, and responsible adoption across Pfizer Global Supply and QSEO. Establishes GxP-compliant AI lifecycle practices, inspection-readiness frameworks, governance forums, portfolio monitoring, inventory management, metrics, and reporting. Advises senior leaders on AI regulations, deployment risks, investment priorities, and compliance while leading cross-functional initiatives and influencing stakeholders across Quality, Digital, Operations, and R&D.

Design and develop production-ready AI and machine learning applications using cloud AI services and end-to-end pipelines. Integrate generative AI, deep learning, neural networks, chatbots, and image processing solutions. Collaborate with stakeholders, optimize model performance and reliability, document technical practices, and mentor junior team members while independently contributing as a subject matter expert.

Develop and productionize AI and machine learning applications using cloud AI services and scalable pipelines. Integrate generative AI, deep learning, neural networks, chatbots, and image processing solutions. Monitor and optimize model performance, manage data preprocessing and evaluation, document technical practices, collaborate with stakeholders, and mentor junior team members.

Develop and deploy production-ready AI and machine learning applications using cloud AI services, generative AI, deep learning, neural networks, chatbots, and image processing. Build scalable pipelines, preprocess data, engineer features, evaluate and optimize models, document technical solutions, collaborate with stakeholders, and guide junior team members.

Develop and deploy production-ready AI and machine learning applications using cloud AI services and generative AI models. Responsibilities include building scalable pipelines, applying deep learning and neural networks, developing chatbots and image-processing solutions, preprocessing data, evaluating and optimizing models, documenting technical designs, collaborating with stakeholders, and mentoring junior team members.

Design and build production-ready AI applications using machine learning, cloud AI services, generative AI, deep learning, neural networks, chatbots, and image processing. Develop scalable pipelines, preprocess data, engineer features, evaluate and optimize models, document technical solutions, collaborate with stakeholders, and guide junior team members.

Design and develop production-ready AI and machine learning applications using cloud AI services and generative AI models. Build scalable pipelines, apply deep learning and neural networks, develop chatbots and image-processing solutions, and optimize model performance. Collaborate with stakeholders, document technical processes, contribute to technical discussions, and mentor junior team members while serving as an independent subject matter expert.

Design and build production-ready AI and machine learning applications using cloud AI services, generative AI, deep learning, neural networks, chatbots, and image processing. Develop scalable pipelines, preprocess data, evaluate and optimize models, document technical solutions, collaborate with stakeholders, and guide junior team members.

Develop and maintain production-ready AI and machine learning applications using cloud AI services, generative AI, deep learning, neural networks, chatbots, and image processing. Responsibilities include designing scalable pipelines, preprocessing data, evaluating and optimizing models, documenting technical solutions, collaborating with stakeholders, and mentoring junior team members.

Leads procurement and third-party management operational excellence initiatives, applying process engineering, project management, analytics, automation, and AI/ML to improve workflows and business outcomes. Coordinates cross-functional workstreams, develops project plans, manages risks and controls, analyzes performance data, prepares dashboards and executive communications, and drives sustainable process transformation across complex organizational environments.

Develop and maintain production-ready AI and machine learning applications using cloud AI services, generative AI, deep learning, neural networks, chatbots, and image processing. Build scalable pipelines, preprocess data, engineer features, evaluate and optimize models, document technical solutions, collaborate with stakeholders, and mentor junior team members.

Develop and maintain production-ready AI applications and pipelines using machine learning, cloud AI services, generative AI, deep learning, neural networks, chatbots, and image processing. Collaborate with stakeholders to translate requirements into technical solutions, monitor and optimize model performance, document designs, and support junior team members.

Bridges data science, engineering, and business teams by identifying AI use cases, translating business goals into analytics solutions, validating AI/ML outputs, communicating insights, and tracking KPIs. Uses SQL, dashboards, and analytics platforms to support telecom business applications and drive adoption of data science solutions.

Develop and enhance custom software solutions using Generative AI and modern development frameworks. Design scalable architectures, apply agile and CI/CD practices, analyze complex problems, and deliver innovative solutions. Collaborate with cross-functional teams to translate requirements into technical implementations, contribute to team discussions, work independently as a subject matter expert, and mentor junior team members.

Build and manage production-grade conversational, generative, and agentic AI applications using Amazon Bedrock, Bedrock AgentCore, and AWS Strands. Lead voice and chat bot development, agent orchestration, prompt engineering, tool calling, evaluation, security, monitoring, optimization, and responsible AI controls. Develop scalable cloud-native architectures using AWS services, improve agent accuracy and reliability, and support enterprise AI governance and performance.

Build and scale machine learning systems for search, including ranking models, feature engineering, model deployment, monitoring, experimentation, and online inference. Design fault-tolerant distributed infrastructure, optimize search latency and throughput, and develop reliable ML services from proof of concept through production. Collaborate across engineering and product teams, communicate technical decisions, review code, document systems, and mentor junior engineers.

Develop complex Power Apps and Power Automate solutions using SharePoint, Dataverse, or SQL backends. Gather business requirements, translate processes into applications and workflows, manage change requests, conduct design reviews, coordinate user acceptance testing, and ensure regulatory compliance. The role also involves advising on enterprise data platforms, integrating systems such as SAP and Salesforce, and supporting business users.

Leads data science projects, develops models and algorithms, analyzes complex datasets, and delivers insights for strategic decision-making. The role ensures data quality, supports experimentation and machine learning applications, collaborates with Product, GTM, Engineering, and data science teams, and mentors junior scientists. Responsibilities include translating analytical findings into business strategies, measuring portfolio performance, and presenting recommendations to senior management.

Develop and deploy enterprise AI and machine learning solutions for banking reconciliation platforms. Build agentic AI, Generative AI, LLM, and RAG applications; integrate full-stack systems; prototype emerging AI technologies; and move solutions from proof of concept to secure, scalable production. Responsibilities include writing production code, establishing technical standards, collaborating with cross-functional teams, and designing performance evaluation metrics for continuous optimization.

Lead complex data discovery, enrichment, curation, and AI-driven research initiatives. Develop scalable workflows for entity resolution, information extraction, taxonomies, ontologies, and knowledge graphs. Collaborate with product teams, customers, and stakeholders to translate data insights into product improvements. Manage end-to-end projects, establish quality standards, mentor junior staff, and drive continuous process improvement.

Perform IP and subsystem-level pre-silicon verification for wireless devices. Develop SystemVerilog and UVM test environments, verification plans, test cases, coverage models, and assertions. Analyze coverage and collaborate with design teams to resolve issues across RTL and gate-level simulations. Apply AI and machine learning tools to improve code generation, debugging, documentation, scripting, and root-cause analysis.

Leads enterprise data engineering and applications development for data reporting, issue management, and transformation initiatives. Oversees data platforms, pipelines, ETL, warehouses, analytics products, data quality, governance, security, and performance optimization. Manages technology roadmaps, stakeholder relationships, delivery governance, platform stability, and large-scale modernization programs while coaching technical teams and ensuring compliance.

Develop and deploy enterprise AI/ML solutions for banking reconciliation platforms. Responsibilities include building agentic AI and Generative AI applications, integrating LLMs and machine learning tools, prototyping emerging AI technologies, writing production code, deploying secure cloud-native services, and evaluating model and agent performance. The role requires expertise in Python, LLMs, RAG, vector databases, GenAIOps, Docker, and AI system architecture.