Top Machine Learning Jobs in India

Develops and deploys machine learning and NLP models, including customer segmentation, lifetime value, and marketing optimization solutions. Responsibilities include data preparation, feature engineering, model training, evaluation, tuning, quality checks, analytics insights, and client deliverables. Translates business requirements into analytical problems, analyzes complex datasets, and contributes to solution methodology and client engagement.

Provides analytics consulting support to Sports and Media clients by extracting insights from data, developing SQL and Python solutions, applying machine learning, creating visualizations and reports, and leading small analytics teams. Collaborates with clients to understand business objectives, communicate findings, improve analytics processes, and support data-driven decisions.

Leads insurance analytics and actuarial regulatory projects, including data modeling, predictive modeling, reporting, visualization, and automation. Manages client and team relationships, project deliverables, stakeholder meetings, issue resolution, and process improvements. Acts as a functional and domain expert while identifying growth opportunities and ensuring industry best practices. Requires strong expertise in SQL, SAS, Python, statistical techniques, and insurance analytics.

Develop and maintain Tableau dashboards, reports, and data models; write complex SQL queries; use Hive and Python for data transformation and automation; conduct ad hoc analysis; validate data accuracy and dashboard performance; and collaborate with stakeholders, data engineers, and data scientists. Payments and fraud experience is preferred, while machine learning knowledge is advantageous.

Leads client-facing banking analytics engagements involving credit risk, fraud detection, or marketing analytics. Builds and validates statistical and machine learning models, translates findings into business recommendations, ensures regulatory compliance, presents insights to clients, and mentors junior team members. Responsibilities include data wrangling, feature engineering, model validation, and analytics project leadership.

Perform end-to-end system verification of Ericsson 5G RAN solutions, including capacity, performance, scalability, mobility, and high-load traffic testing. Analyze logs, traces, KPIs, and protocol-layer behavior; troubleshoot PHY/MAC/RLC/PDCP/IP issues and identify root causes. Support feature integration, test automation, verification frameworks, and CI/CD improvements. Collaborate with development, integration, CI, and product teams while applying modern and AI-assisted verification methods.

Leads Sulzer’s Advanced Analytics and AI function, converting business opportunities into governed, production-grade statistical, machine-learning, GenAI, and agentic-AI solutions. Owns the service portfolio, delivery standards, lifecycle, adoption, monitoring, partner model, and production value metrics. Builds and coaches internal teams, collaborates with senior stakeholders and enterprise architecture, and ensures data quality, security, privacy, responsible AI, and operational safety requirements are met.

Lead the design, development, deployment, and optimization of production-grade Generative AI systems. Build RAG pipelines, fine-tune foundation models, develop AI agents, establish evaluation and observability frameworks, and integrate multimodal AI capabilities. Collaborate with product, engineering, data, and business stakeholders to deliver scalable, reliable, secure, and responsible AI solutions.

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.

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.

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.

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.

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 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.

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.

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.

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 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.

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.

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.