Top Machine Learning Jobs in India

Collect, clean, model, and analyze marketing data to generate customer, campaign, and market insights. Lead predictive analytics, machine learning, A/B testing, visualization, and reporting efforts to optimize targeting and communications. Present actionable recommendations to stakeholders and partner with Marketing, Data Product, Coverage, and MarTech engineering teams. The role also involves influencing decisions, managing risk and controls, and potentially leading and developing team members.

Develop and maintain automated quality testing for enterprise data products, pipelines, transformations, APIs, and platform capabilities. Validate data correctness, completeness, freshness, consistency, and lineage; build reconciliation and monitoring frameworks; design regression suites; and investigate production data-quality issues. The role also evaluates AI-powered analytics capabilities by validating user intents, creating evaluation datasets, measuring response accuracy, and identifying hallucinations and edge cases.

Own the strategy, roadmap, lifecycle, adoption, and business outcomes for core CRM capabilities serving automotive dealerships. Lead customer-centric, data-driven product development across Engineering, Design, Data, GTM, and Customer Success. Manage Product Managers, align distributed teams and stakeholders, define success metrics, guide prioritization, and deliver scalable SaaS solutions. Preferred experience includes AI/ML product management and automotive retail or dealer/OEM data expertise.

Owns strategy, roadmap, and end-to-end delivery for automotive Parts product capabilities, including AI-powered workflows, OEM and third-party integrations, and REST API extensibility. Partners with engineering, ML/AI, design, data, GTM, and customer teams to improve dealership productivity, adoption, workflow efficiency, integration reliability, and customer outcomes.

Own dealer-facing product features and integrations for Tekion’s GM Digital Retail Platform. Translate OEM requirements into product specifications, API contracts, user stories, and engineering deliverables. Manage the scrum backlog, coordinate Engineering, GM, Design, and Dealer Success stakeholders, monitor adoption and integration metrics, troubleshoot data-sync issues, and support rollout, compliance, and certification readiness.

Provides strategic and operational leadership for multiple engineering teams, overseeing technical execution, product delivery, team structure, hiring, talent development, engineering quality, scalability, automation, and platform modernization. Collaborates with product, design, architecture, and operations leaders on technical strategy and roadmaps while coaching engineering managers and senior engineers.

Leads large-scale, cross-functional technical programs from planning through delivery. Partners with Product, Engineering, Infrastructure, Security, and operational teams to define scope, manage risks and dependencies, establish reporting cadences, and deliver initiatives on schedule. The role also drives strategic roadmapping, stakeholder alignment, executive communication, and mentorship of junior technical program managers.

Build and own automated quality engineering for Tekion’s AI Platform, including APIs, SDKs, data and feature pipelines, model serving, deployment, LLM gateways, and vector stores. Design regression, performance, scalability, reconciliation, and reliability testing; validate ML data flows and platform SLOs; develop evaluation frameworks; use LLMs to accelerate test creation; and lead root-cause analysis and preventive improvements across platform and infrastructure teams.

Leads and manages a team of applied scientists developing scalable AI and machine learning solutions. Owns research and product roadmaps, customer-facing deliverables, technical architecture, and full ML lifecycle execution from data collection through deployment and monitoring. Partners with product, engineering, business, and customer success teams to align priorities, deliver measurable business impact, and promote best practices in model development, experimentation, scalability, and technical excellence.

Leads the Service product portfolio strategy and lifecycle, including AI-native agents and intelligent workflows for automotive service and repair operations. Owns product vision, market analysis, KPIs, pricing, packaging, monetization, and business outcomes. Partners with engineering, design, marketing, data science, and business teams to launch products and drive adoption. Manages and mentors a large product team while improving product development processes.

Lead product strategy and execution for accounting and financial products serving automotive dealerships. Own the roadmap, customer research, product requirements, metrics, and end-to-end delivery of scalable B2B SaaS solutions. Partner with engineering, design, finance, compliance, marketing, analytics, and external stakeholders to improve financial workflows, including ledger management, reconciliation, settlement, reporting, payables, and receivables. Drive innovation, automation, product quality, and measurable customer impact.

Provides technical leadership for designing and building scalable, high-performance software systems. Leads complex engineering initiatives, designs distributed system components, partners with product and cross-functional teams, promotes engineering best practices, mentors developers, and resolves system-wide issues through root cause analysis. The role requires strong expertise in cloud-native development, containerization, scalability, fault tolerance, observability, and large-scale application delivery.

Own product strategy, roadmaps, feature development, and launches while collaborating with engineering, design, marketing, sales, and customer success. Gather customer and market insights, analyze competitive and usage data, prioritize initiatives, manage cross-functional dependencies and risks, define success metrics, and ensure product outcomes align with business objectives. The role also contributes to product management frameworks, tools, and best practices.

Build automated quality and evaluation frameworks for ML models, AI agents, LLM applications, prompt pipelines, RAG systems, and APIs. Develop evaluation datasets, regression suites, scoring pipelines, monitoring, guardrails, and model quality metrics. Investigate hallucinations, drift, behavioral regressions, and production issues while partnering with ML, data, product, and applied AI teams to improve reliability.

Own the strategy, roadmap, lifecycle, and outcomes for core CRM capabilities serving automotive dealerships. Drive customer adoption, engagement, conversion, and satisfaction through data-informed prioritization and scalable platform development. Lead cross-functional initiatives across Engineering, Design, Data, GTM, Marketing, and Customer Success; align stakeholders, manage dependencies, and mentor Product Managers. Translate customer and market insights into product decisions while balancing near-term execution with long-term platform strategy.

Own product strategies, roadmaps, and feature development for assigned product lines. Collaborate with engineering, design, marketing, sales, and customer success to launch solutions, gather customer feedback, analyze market and usage data, manage cross-functional dependencies, and define measurable outcomes aligned with business goals.

Own the end-to-end lifecycle and strategy for AI/ML-powered automotive service capabilities spanning scheduling, repair orders, parts, technician workflows, and invoicing. Partner with ML and engineering teams to prioritize use cases, define success metrics, design scalable systems, and establish product architecture standards. Use data to guide roadmaps and improve accuracy, adoption, workflow efficiency, and time savings across dealership operations.

Leads Medline’s India AI and Automation organization, strategy, governance, engineering practices, and enterprise solution portfolio. Builds multidisciplinary teams, drives AI adoption, oversees solutions from discovery through production and value realization, and ensures secure, scalable, reliable delivery. Guides capabilities spanning generative and agentic AI, machine learning, RPA, intelligent document processing, cloud platforms, MLOps, LLMOps, and automation while partnering with global stakeholders and business leaders.

Develop and deploy AI-driven product features using machine learning, NLP, and generative AI. Build end-to-end ML pipelines, integrate models into production microservices and APIs, analyze data, optimize model performance, and contribute to testing, documentation, technical reviews, and cross-functional product delivery.

Build and productionize machine learning, LLM, and AI solutions with Data Science teams. Design industrialized data-processing pipelines, implement MLOps and LLMOps frameworks, manage model lifecycles, and develop production Python, ML, and cloud solutions using Azure, GCP, Databricks, Spark, and PySpark. Gather requirements, estimate work, document solutions, present results, and support technical best practices.

Owns product strategy and execution for programmatic ad monetization, including demand prioritization, auctions, pricing, ad delivery, partner integrations, yield optimization, analytics, new ad formats, and AI-driven monetization capabilities. Partners with Engineering, Data, Business, Operations, and external providers to launch scalable products and improve revenue efficiency, ad quality, and user experience.

Own full-chip physical verification and signoff for advanced GPU and SoC designs from block assembly through tapeout. Responsibilities include DRC, LVS, antenna verification, 3D die-stacking validation, advanced-node signoff, AI-powered automation, flow development, and cross-functional design closure. Requires expertise in physical design verification, VLSI concepts, signoff tools, and RTL-to-GDSII implementation processes.

Designs, implements, validates, and deploys complex statistical and machine learning models to solve business problems. Partners with architects and domain experts to enable data flow, prototype solutions, and productionize models. Mentors junior staff, communicates results to stakeholders, and advances team capabilities through knowledge sharing.

Develop production-ready AR/VR models and digital content for vehicle aftersales applications. Build systems using Unity and Unreal Engine, interpret wiring diagrams, integrate sensor data, and apply sensor fusion techniques. Develop computer vision and machine learning models using Python and relevant frameworks, with advanced knowledge of supervised, unsupervised, and reinforcement learning. Produce high-quality production code in C#, C++, and Python for AR/VR vehicle servicing solutions.

Analyzes recurring operational issues and data to identify root causes, then translates business rules into AI requirements, prompts, validation checks, and test cases. Collaborates with Product, Engineering, AI/ML, and Implementation teams to improve extraction, mapping, classification, and automation workflows. Evaluates LLM outputs, identifies failure patterns, builds reusable AI workflows and evaluation datasets, measures accuracy and efficiency improvements, and documents reusable solutions.