Top Machine Learning Jobs in Chennai

Own customer service requests from contract validation through resolution, including emergency network restoration, SLA and KPI oversight, proactive fault prevention, data-driven support, and customer-network software implementations. Diagnose unsuccessful software loads, implement corrective actions, improve support processes, and build customer relationships through consultation, negotiation, knowledge sharing, and change management.

Leads data engineering teams and provides technical direction for scalable, reliable data platforms and solutions. Oversees Agile delivery, backlog planning, operational support, quality standards, technical debt reduction, and stakeholder communication. Coaches engineers, sets performance goals, drives innovation, and guides adoption of data, cloud, containerization, DevOps, artificial intelligence, and machine learning technologies.

Design and maintain scalable ETL/ELT pipelines, data warehouses, and big data infrastructure. Optimize databases and workflows, implement data quality and governance frameworks, automate testing and deployment, troubleshoot complex data issues, and ensure reliable systems. Collaborate with data scientists, analysts, and business teams to support analytics and machine learning. Mentor junior engineers and establish data engineering best practices.

Lead the delivery of AI products across international markets by coordinating internal engineers, contractors, and vendors. Establish engineering standards, make technical decisions, review code, ensure testing and release readiness, and guide solutions from proof of concept through enterprise production. Oversee data, AI, generative AI, agentic AI, and full-stack applications while managing dependencies, technical debt, and delivery quality. Collaborate with product, engineering, data science, security, and global stakeholders, and evaluate emerging technologies.

Build, deploy, monitor, and retrain machine learning models for ETA forecasting, status extraction, and logistics automation. Develop regression, classification, time-series, NLP, and LLM-based solutions using noisy supply chain data. Own production ML pipelines, diagnose offline-to-live performance gaps, and measure business impact. Collaborate with product, engineering, and operations teams while mentoring data scientists and making architecture and build-versus-buy decisions.

Design, train, evaluate, and deploy ML and DL models (classification, regression, clustering). Perform feature engineering, EDA, and preprocessing. Use PyTorch/TensorFlow and model interpretability tools (SHAP). Build end-to-end ML pipelines, run experiments, and work on GenAI/LLM use cases (embeddings, summarization, transformer architectures). Collaborate to productionize models and write clean, well-documented Python code.

Lead design, develop, test, and deploy scalable Java/Spring Boot cloud-native applications on AWS/Azure. Integrate AI/ML, build full-stack solutions with ReactJS, enforce code quality, mentor engineers, champion DevOps/security practices (Kubernetes, Docker, CI/CD, Git), and design compliant KYC/AML banking solutions.

Develops and validates credit risk models using statistical, machine learning, and AI techniques. Builds analytical solutions with GCP, SAS, R, and Python; analyzes modeling results and translates findings into business insights. Responsibilities include credit lifecycle analysis, special studies, process improvement, documentation, presentations, stakeholder collaboration, and managing project deliverables. Requires advanced quantitative education, knowledge of PD, LGD, and EAD modeling, predictive modeling, cloud analytics, and strong communication skills.

Entry-level engineering role involving C-based device development for networking, Wi-Fi, home gateways, and IoT systems. Responsibilities may also include manual and automated wireless testing across functional, regression, and performance areas, plus Python-based AI/ML work involving mathematical foundations, feature engineering, neural networks, and machine learning models. The role requires a bachelor’s engineering degree and a six-month full-time internship before potential full-time employment.

Develop artist-facing and backend tools that extend SideFX Houdini and integrate with VFX and CG production pipelines. Build clean, testable, maintainable software using HOM, HDK, Python, and/or C++. Collaborate with artists, developers, and project managers across the software lifecycle, while emphasizing usability, documentation, UX, reliability, and adoption. Support procedural workflows, production tools, simulations, rendering, and distributed studio systems.

Build Python-based tools for layout, animation, matchmove, and previs artists working with complex CG scenes. Develop scene-management systems, asset and animation library integrations, and 3DEqualizer data import/export workflows. Collaborate with product owners and stakeholders in an Agile environment, contributing across design, development, maintenance, and pipeline integration. Work may include front-end and back-end development for high-end VFX and feature animation pipelines.

Develop artist-facing and backend tools that extend Autodesk Maya and integrate with VFX and CG pipelines. Build reliable, maintainable software using HOM, HDK, Python, C++, MEL, and Maya APIs; improve workflows, usability, and adoption; and collaborate with artists, developers, and project managers throughout the software lifecycle. The role also involves documentation, testing, deployment, support, roadmap planning, and innovation across distributed VFX production teams.

Leads strategy, roadmap, and end-to-end development of ML-powered generative AI products. Defines requirements, prioritizes backlogs, integrates ML models into scalable experiences, tracks product metrics, evaluates emerging technologies, and coordinates cross-functional teams spanning ML research, engineering, data, UX, and creative functions.

Manage engineering change orders across global manufacturing sites using Agile PLM and BAAN. Create product numbers, BOMs, part numbers, approved vendor lists, and production releases for new products. Coordinate with engineering, materials, customers, and cross-functional teams during NPI. Generate reports, resolve service issues through root cause analysis, train team members, manage escalations, and implement continuous process improvements.

Manage engineering change orders, product data, bills of materials, part numbers, approved vendor lists, and production releases using Agile PLM and BAAN. Support NPI activities, customer documentation, reporting, root-cause analysis, process improvements, audits, and procurement-process efficiency. Collaborate with engineering, materials, customers, sites, and cross-functional teams while mentoring staff, handling escalations, and training team members.

Build and lead OneMagnify’s global FP&A Reporting Center of Excellence in India. Own executive, board, lender, and management reporting; establish scalable standards, controls, and processes; oversee budgeting, forecasting, variance analysis, and cost optimization; recruit and develop FP&A talent; and drive finance transformation through automation, Adaptive Planning, AI, and modern reporting technologies.

Supports engineering change management and new product introduction in an electronics manufacturing environment. Creates BOM part numbers and approved vendor lists, releases customer documents and part lists, reviews ECOs and drawings, coordinates with process, product engineering, and materials teams, responds to stakeholder queries, and tracks process metrics.

Lead engineering strategy, teams, architecture, delivery, and platform outcomes for the Unify Energy SaaS platform. Oversee software, data, integrations, automation, security, reliability, and applied AI capabilities supporting oil and gas information workflows. Partner with product, customers, implementation, and business leaders to prioritize investments, improve delivery predictability, strengthen platform quality, and achieve measurable customer, operational, and financial results.

Manage engineering change orders across global manufacturing sites using Agile PLM and BAAN. Create product numbers, BOMs, part numbers, and approved vendor lists; release documentation and parts to production. Support NPI change analysis, reporting, process improvements, root-cause analysis, customer coordination, escalations, mentoring, and training. The role requires electronics engineering experience in manufacturing, strong analytical and communication skills, and night-shift availability.

Develops, deploys, monitors, and maintains machine learning pipelines and algorithms. Performs exploratory data analysis, feature extraction, modeling, tuning, experiment tracking, anomaly detection, classification, clustering, and forecasting. Translates business requirements into analytical problems, evaluates solutions, mentors junior professionals, and communicates findings to technical and non-technical stakeholders. May lead projects and contribute to Agile development processes.

Serve as primary customer contact for FourKites' SaaS platform: troubleshoot, replicate, and track product issues; coordinate with Development, QA, and Consulting; provide regular client updates; participate in weekend emergency rotation; and contribute to AI-driven support initiatives.

Lead the architecture and development of scalable AI infrastructure, distributed microservices, real-time data pipelines, and agentic AI systems for intelligent networking. Drive the full software lifecycle from design through production operations, establish technical direction, mentor engineers, and improve system reliability, security, observability, performance, and scalability.

Lead the technical vision, architecture, development, testing, deployment, and operations of scalable AI infrastructure, distributed microservices, real-time data platforms, and agentic AI systems. Build secure, resilient, observable services processing high-volume network data; guide technical strategy, improve engineering practices, and mentor engineers. Translate complex technical challenges into production-ready solutions across intelligent networking, cloud platforms, analytics, and automation.

Lead the architecture, development, testing, deployment, and operation of scalable AI infrastructure, distributed microservices, real-time data platforms, and agentic AI systems. Define technical vision, build secure and observable high-performance services, process large-scale network data, and integrate intelligent networking capabilities. Mentor engineers, lead technical discussions and reviews, improve system reliability and performance, and translate complex technical challenges into production-ready solutions.

Lead the architecture and development of scalable, secure, observable AI infrastructure, distributed microservices, real-time data pipelines, and agentic systems for intelligent networking. Drive technical vision, software delivery, system reliability, and operational excellence while mentoring engineers. Build production platforms processing high-volume network and operational data, integrating cloud infrastructure, machine learning, telemetry, and automation capabilities.