Top Machine Learning Jobs in Pune

Develops and productionizes machine learning and data science solutions for Mastercard’s Business & Market Insights products. Responsibilities include feature engineering, model training and deployment, exploratory analysis, large-scale PySpark processing, advanced SQL, pipeline optimization, responsible AI controls, and product innovation. Partners with product, engineering, sales, and clients to prioritize solutions, deliver milestones, incorporate feedback, and improve products. Provides technical leadership and mentorship to junior data scientists.

Leads data science and AI/ML product development, designing, productionizing, and optimizing traditional machine learning and generative AI solutions. Builds LangChain and LangGraph applications, processes large datasets with PySpark and SQL, evaluates model quality and performance, and applies privacy, security, responsible AI, monitoring, and explainability controls. Partners cross-functionally on product strategy, mentors data scientists, establishes reusable technical practices, and drives releases and continuous product improvement.

Develops and productionizes machine learning and data science solutions for Mastercard’s Business & Market Insights products. Responsibilities include feature engineering, model training, evaluation, deployment, exploratory analysis, large-scale data processing with PySpark, advanced SQL, and scalable ML workflows. The role partners with product, engineering, client services, and sales teams to deliver analytics-driven products, evaluates AI/ML approaches, drives product improvements, and mentors junior data scientists.

Develop statistically effective algorithms and apply machine learning, hypothesis testing, data mining, and retrieval techniques to analyze complex datasets. Identify trends, create visualizations, communicate findings to clients and stakeholders, and evaluate emerging datasets and technologies. The role requires collaboration across consulting and analytics teams, with opportunities to build scalable solutions using generative AI, deep learning, big data, and cloud technologies.

Leads client-facing AI and digital transformation engagements from strategy through implementation and adoption. Manages cross-functional teams building enterprise Generative AI, Agentic AI, machine learning, and analytics solutions. Advises senior stakeholders, develops client relationships, supports business development, manages budgets and vendors, ensures engineering and architecture quality, hires and mentors talent, and drives AI scaling initiatives across consulting engagements.

Leads and develops a Data Science team, oversees predictive and machine learning model delivery, establishes governance and lifecycle standards, and partners with business, engineering, and analytics leaders. Translates complex data into executive insights, frames ambiguous business problems, improves analytical processes, ensures production-ready models, and measures business impact while developing technical talent and promoting responsible, explainable analytics.

Develop and scale globally relevant data analytics and agentic AI products for enterprise and credit risk customers. Partner with analytics, machine learning, engineering, operations, legal, customer experience, commercial, and product teams. Gather customer feedback, analyze data, define product direction, create requirements and user stories, communicate product updates and risks, and support go-to-market initiatives throughout the product lifecycle.

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.

Leads technology risk, application security, AI governance, and compliance assessments across applications, cloud services, platforms, third parties, and AI solutions. Defines assessment scope, evaluates controls and residual risk, documents findings, oversees remediation, supports incidents, and provides management reporting. The role also contributes to security policies, assessment methodologies, DevSecOps governance, secure software development, AI risk management, and continuous improvement while collaborating with technical, legal, privacy, compliance, and business stakeholders.

Develop advanced data science algorithms, apply statistical and machine learning techniques to large datasets, evaluate emerging data technologies, and build scalable generative AI and deep learning solutions. Collaborate with clients and engineering teams to communicate findings, deploy models into production, and maintain reliable workflows using software engineering best practices.

Leads software engineering squads delivering scalable, high-performing products. Responsibilities include architecture and system design, full-stack development, prioritization, cross-functional coordination, mentoring, quality and security oversight, automation, testing, root-cause analysis, operational excellence, and continuous improvement across the software development lifecycle.

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.

Provides technical support for a cloud-based analytics application by investigating customer-reported issues, performing log analysis and root cause investigations, troubleshooting SQL and database performance, managing tickets and SLAs, coordinating with engineering and product teams, communicating issue status, and creating knowledge-base articles. The role includes shift rotations and requires strong customer communication, Unix troubleshooting, REST API and SSO knowledge, and familiarity with application servers and business intelligence concepts.

Designs data-driven digital products, prototypes, dashboards, applications, chatbots, and interfaces using human-centered design, Lean UX, and Design Thinking. Leads workshops, develops personas and user journeys, creates visual and interaction designs across web, mobile, and IoT, and collaborates with product, technology, marketing, and regional teams. Conducts iterative user testing, contributes to design systems, and shapes AI- and ML-enabled experiences while balancing usability, business goals, regulatory compliance, and global user needs.

Leads data analytics for Financial Crime Agile Testing, defining hypotheses, testing plans, data requirements, and analytical approaches. Oversees SQL, Python, and SAS analytics, quality-controls scripts and outputs, evaluates data quality and control effectiveness, and communicates findings to stakeholders. Provides technical guidance and escalation support to analysts, contributes to methodology improvements, and ensures independent, risk-based, reproducible testing with appropriate documentation, evidence retention, and data-privacy compliance.

Lead end-to-end solution architecture for Java and Spring Boot microservices, cloud-native platforms, full-stack applications, and event-driven systems. Drive modernization, cloud migration, security, scalability, and resilience initiatives across Azure or AWS environments. Produce architecture deliverables, incorporate AI capabilities, collaborate with product and engineering stakeholders, and mentor senior engineers while guiding enterprise technology decisions.

Develop an externally funded biomedical engineering research program, conduct interdisciplinary research in biomedical imaging and bioinstrumentation, teach undergraduate and graduate courses, mentor students, contribute to curriculum development, and collaborate across engineering, medicine, and computational science disciplines.

Develop and deliver scalable, secure software and large-scale RPA automations using UiPath. Design process automation architectures, integrate REST and SOAP services, manage releases and version control, monitor performance, handle incidents, and conduct root-cause analysis. Collaborate with cross-functional stakeholders, promote code quality and secure coding, mentor developers, and help lead technical teams. The role is based in Pune and requires a bachelor’s degree in computer science, IT, or engineering.

Leads enterprise data quality strategy, architecture, platforms, frameworks, observability, governance, and automation. Designs reusable quality capabilities for batch, streaming, cloud, on-premises, and SaaS environments; establishes rules, metrics, alerts, and remediation workflows; integrates quality with metadata, lineage, catalogs, MDM, and data contracts; mentors engineering teams; evaluates tools; and applies AI and machine learning to anomaly detection, root-cause analysis, and trusted AI-ready data platforms.

Develop machine learning and statistical models for propensity modeling, customer analytics, segmentation, sentiment analysis, and emerging AI/LLM use cases. Analyze large customer datasets, engineer features, validate models, and evaluate performance. Translate business challenges into data-driven strategies, identify growth opportunities, and present insights to clients and senior stakeholders while collaborating with cross-functional teams.

Develop machine learning and statistical models for propensity modeling, customer analytics, segmentation, sentiment analysis, and emerging AI/LLM applications. Analyze large customer datasets, perform feature engineering and model validation, and translate findings into business strategies. Present actionable insights to clients and senior stakeholders while collaborating with cross-functional teams. The role requires strong Python, SQL, cloud analytics, customer data platform, communication, and stakeholder management skills.

Develop and deploy AI and machine learning solutions for DNV’s maritime business processes. The role covers stakeholder engagement, data analysis, technical architecture, experimentation, programming, testing, DevOps release cycles, and production integration. The successful candidate will identify new applied AI opportunities, collaborate with data scientists, developers, engineers, and domain experts, and contribute to business value through practical AI systems.

Leads development of secure, scalable software services and applications using Java, Spring, Kafka, APIs, and distributed-system patterns. Owns complex cross-service problems, architecture, prioritization, automation, integration, troubleshooting, incident analysis, and operational excellence. Mentors engineers, guides technical decisions, promotes secure coding and quality practices, partners with product teams, supports agile delivery, and conducts technical interviews.

Develop and validate AI and machine learning models across credit risk, marketing, fraud, and account management domains. Use GCP to automate workflows, prepare training data, develop algorithms, and execute AI validation projects. Collaborate with stakeholders across geographies, support model risk management policies, ensure regulatory compliance, and apply industry best practices. The role requires advanced Python and SQL skills, model validation experience, and knowledge of financial risk models.

Lead automation and analytics for internal audit: design Power BI dashboards, data analytics, and AI/RPA pilots to enhance SOX testing, control validation, anomaly detection, and continuous monitoring. Liaise with IT, business, and external auditors; coach team members; support remediation and audit transformation.