Top Machine Learning Jobs in India

Design and lead enterprise AI solutions using Microsoft Copilot, AI Agents, and Azure OpenAI. Collaborate with stakeholders to define roadmaps, provide technical leadership, ensure scalability, security, governance, and drive AI-driven automation and decision intelligence across systems.

Lead and develop engineering managers across multiple teams, own org design and multi-quarter engineering strategy, ensure delivery/operational health, drive resourcing and budget decisions, represent engineering in senior cross-functional forums, and build a leadership pipeline for a large-scale consumer product organization.

Lead design of credit underwriting strategies and customer journeys across digital and phygital channels; perform market and portfolio analytics to identify growth and risk reduction levers; build acquisition and behavioral scorecards; design experiments for new channels; track credit risk performance and diagnostics; manage 2-3 analysts while leveraging Python, SQL, Excel, visualization and ML techniques.

Lead statistical strategy and delivery for Phase I-IV clinical trials embedded with a pharmaceutical sponsor. Design analyses, support protocol and reporting activities, oversee programming/CRO work, apply SAS/R (R Shiny)/Python and ML/DL methods for analyses and automation, and mentor junior statisticians.

Lead the risk product suite roadmap and execution for merchant onboarding, fraud prevention, and credit risk. Manage a risk engineering and data science squad, build real-time risk engines and ML models, optimize KYC/KYB onboarding flows, and develop lending/settlement risk models to minimize financial loss while preserving merchant and buyer experience.

Lead vision, strategy, and execution for a retail experimentation SaaS platform. Define roadmap, translate customer needs into product requirements, collaborate with engineering and data science, measure experiment impact, and drive adoption across go-to-market teams.

As a CRO Expert, you will use data-driven strategies to optimize user experience and conversion rates while crafting experiments and deriving actionable insights.

Lead algorithm design and development for wafer inspection products, delivering image processing, computer vision, and machine learning solutions. Define performance requirements, mentor engineers, support system integration, validate and deploy algorithms, and ensure software quality and reliability.

Lead strategic analytics for eBay’s Trust & Risk organization. Develop enterprise measurement frameworks, KPIs, and decision models for customer trust, transaction risk, losses, false positives, and ROI. Identify and prioritize high-impact opportunities, guide multiple analytical workstreams, influence senior cross-functional leaders, and translate complex data into business strategy. Mentor analysts and data scientists while driving measurable improvements in customer experience, risk outcomes, policy effectiveness, and financial performance.

Design and develop scalable Python-based industrial IoT solutions, including backend services, REST APIs, data pipelines, ETL processes, and time-series analytics applications. Build machine-learning and deterministic algorithms, write comprehensive tests, deploy solutions on Azure Functions and Azure Databricks, troubleshoot production issues, and collaborate with global agile teams to deliver reliable digital products.

Lead enterprise data modernization across Databricks, Snowflake, and AWS. Define target-state architectures, Medallion data models, governance frameworks, CI/CD pipelines, and scalable batch, streaming, and CDC ingestion. Build secure, high-performance data foundations for analytics, machine learning, and Generative AI, including vector storage and feature layers. Establish architecture standards, optimize platform performance, collaborate across technical teams, and advise clients on data strategy and roadmaps.

Develops and governs AI capabilities for Finance by identifying use cases, designing automation and AI-enabled workflows, validating data and models, integrating AI with analytics platforms, and ensuring controls, compliance, monitoring, and human oversight. The role bridges Finance and IT, supports transformation programs, creates prompts and user enablement materials, manages stakeholders, and coordinates project governance. It requires finance process expertise, machine learning knowledge, analytics proficiency, project management skills, and willingness to travel.

Develop predictive models, NLP and machine learning systems using large user datasets to improve search, matching, recommendations, and other digital products. Build scalable data products with Engineering and Product teams, applying statistical analysis, vector search, LLM/RAG techniques, embeddings, classifiers, and deep learning. Collaborate across teams to research new methods and deliver production-ready software.

Develop predictive models, NLP and machine learning systems using large user datasets to improve products and create new data products. Responsibilities include statistical analysis, scalable data system development, prompt engineering, large language model benchmarking, and agentic workflow experimentation. The role collaborates with Engineering, Product, BI, Legal, and Management teams and may involve production model deployment and backend development.

Leads a global portfolio of process and analytics initiatives across pharmaceutical operations. Owns opportunity prioritization, value realization, project delivery, governance, risk management, stakeholder alignment, change adoption, and talent coaching. Uses process mining, automation, AI, and advanced analytics across SAP, Veeva, and Salesforce to improve efficiency, reduce risk, and deliver measurable financial and operational outcomes.

Leads ERP risk advisory engagements involving implementation risk assessments, security and controls design, GRC, segregation of duties, data analytics, automation, and data validation. Manages multiple client projects, oversees India-based team quality, mentors staff, supports practice growth and sales, maintains client relationships, and ensures engagement documentation and delivery meet firm standards. The role also contributes to risk consulting strategy, business development, training, and continuous auditing and monitoring programs.

Administers and governs Support, Cloud Operations, and Customer Success analytics tools and processes. Builds accurate dashboards, reports, and performance metrics using Tableau, Looker Studio, BigQuery, Jira, SQL, and Excel. Applies machine learning, NLP, predictive analytics, and generative AI to identify trends, analyze support interactions, automate workflows, and deliver proactive insights. Monitors data quality, investigates processing issues, supports audits, prepares ROI and accrual reports, and leads selected departmental initiatives.

Leads the design, development, and delivery of scalable Python applications and cloud-native services. Defines architecture and technical standards, ensures code quality and application reliability, and resolves complex technical issues. Mentors developers, manages technical delivery, collaborates with cross-functional stakeholders, and supports Agile/Scrum planning and releases. The role also promotes responsible AI-assisted development and may work with data engineering technologies, messaging systems, observability tools, and machine learning frameworks.

Own moderately complex customer engagements from configuration and integration through deployment and incident response. Build AI-enabled solutions, automation, reusable integration patterns, documentation, and operational runbooks. Troubleshoot customer issues, assess technical risks, coordinate with internal teams, and mentor newer Customer Engineers. The role requires autonomy, strong customer communication, enterprise platform expertise, and hands-on experience with APIs, integrations, and deployments.

Lead design, development, and operation of production-grade AI/ML solutions (LLMs, RAG, multi-agent systems). Define architecture, metrics, and evaluations. Implement MLOps, CI/CD, monitoring, and cloud deployments. Mentor junior engineers and align AI capabilities with product needs.

Designs and governs enterprise hyperautomation solutions using AI/ML, RPA, process mining, IPA, cloud infrastructure, data platforms, and integration technologies. Leads architecture across complex global initiatives, establishes standards and compliance processes, optimizes solution performance, manages risks, collaborates with vendors and stakeholders, documents solution blueprints, and provides technical leadership and mentorship to architects and partners.

Leads technical Developer Relations for NVIDIA AI platforms across India's financial services AI labs. Builds adoption strategies, technical demos, benchmarks, reference architectures, workshops, and performance guides. Works directly with researchers, infrastructure teams, and CTOs to profile workloads, optimize inference, debug integrations, and design secure, observable GPU deployments across cloud, data centers, Kubernetes, and hybrid environments. Translates developer feedback and workload requirements into product and engineering input.

Leads the architecture, technical enablement, and delivery of advanced BI, machine learning, conversational AI, and data-platform capabilities. Defines reusable engineering patterns, semantic-layer strategies, operationalization frameworks, and BI integrations with CRM and business systems. Oversees innovation initiatives, evaluates emerging technologies, and guides cross-functional architecture and platform work. Manages and mentors principal engineers while influencing BI developers, data scientists, and data engineers. Promotes governance, security, observability, lifecycle management, and technical excellence across a global BI organization.

Lead the global architecture, governance, implementation, integration, and optimization of SAP Transportation Management solutions. Design transportation and logistics processes, SAP BTP extensions, API- and event-driven integrations, and AI-enabled optimization strategies. Oversee SAP TM integration with S/4HANA, EWM, GTS, BN4L, carriers, and third-party platforms. Provide technical leadership, resolve critical issues, guide architecture decisions, and mentor cross-functional teams across global transformation programs.

Leads KKR’s Performance Analytics function, owning private-market performance methodologies, models, validation, reconciliation, attribution, benchmarking, credit analytics, reporting, and automation. Builds production-quality Python and SQL solutions while managing and mentoring approximately three analysts and associates. Partners with investment, Finance, Investor Relations, Fund Accounting, data engineering, and technology teams to deliver reliable fund, deal, asset, and investor-level analysis.