Top Machine Learning Jobs in Pune

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.

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 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.

Senior Product Manager responsible for defining and delivering shared services for SailPoint’s enterprise identity security platform. The role partners with Product, Design, Engineering, and stakeholders to guide SaaS and cloud capabilities from discovery through launch, prioritize roadmaps, define requirements, track adoption metrics, and shape long-term platform strategy. The position is hybrid in Pune and requires approximately 15% travel.

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.

Develops and integrates radiating components and passive radiation-pattern structures for multiband base-station antennas. Responsibilities include 3D and 2D electromagnetic simulation, prototype RF measurements, performance optimization, troubleshooting, technical documentation, and supporting the product lifecycle through mass production. The role collaborates with international cross-functional teams and requires relocation to Rosenheim, Germany.

Lead end-to-end delivery of large, complex technical epics and engineering initiatives. Manage engineering teams, dependencies, risks, milestones, releases, governance, and stakeholder communications. Partner with engineering, architecture, product, business, and delivery teams to ensure predictable, high-quality outcomes. Facilitate Agile practices, resolve impediments, establish accountability, and translate technical information into business insights. Experience delivering AI, machine learning, cloud, data, API, or enterprise-scale initiatives is advantageous.

Owns a cybersecurity detection coverage area, including backlog prioritization, technical direction, detector design, implementation, code reviews, tuning, and performance measurement. The role improves detection fidelity, ATT&CK coverage, false-positive reduction, and regression prevention while translating threat intelligence, threat hunting, and SOC feedback into roadmap priorities. It requires deep expertise in at least one detection domain and hands-on detector-as-code development with version control and controlled deployment.

Leads mainframe modernization and migration initiatives for large global clients. Develops transformation and re-platforming solutions, conducts discovery workshops, presents technical and business cases, advises executives, and partners with sales, consulting, operations, and product teams. Requires extensive mainframe expertise across legacy technologies, migration architecture, data modernization, cloud and hybrid environments, and enterprise hosting. The role also supports AI-driven modernization, technical documentation, project lifecycle management, and client relationship development.

Develops hardware-accelerated AI software for multimedia platforms, including audio, video, augmented reality, computer vision, and streaming applications. Responsibilities include designing algorithms, deploying applications across platforms, profiling and optimizing AI pipelines, addressing system-level resource challenges, and writing Python and C++ code. Requires substantial Linux software development experience, cloud-native architecture knowledge, and expertise in computer vision, machine learning, and deep learning.

Lead enterprise AI initiatives from discovery through deployment, translating business requirements into technical roadmaps and delivering scalable software solutions. Collaborate with product, engineering, and data science teams in agile environments, lead technical assignments, manage stakeholders, promote secure coding and testing practices, and navigate governance requirements in a regulated environment.

Leads data science, AI, and machine learning capabilities across enterprise platforms. Develops cloud-based content classification systems, governs content lifecycle and metadata enrichment, embeds AI intelligence into product roadmaps, and creates agentic AI frameworks. Partners with product, engineering, and domain teams to align technical execution with business goals while mentoring operations and enablement teams.

Builds and optimizes AI Operations solutions for IT processes, including incident management, root cause analysis, monitoring, anomaly detection, and infrastructure problem resolution. Develops and deploys machine learning models, AI agents, and CI/CD pipelines while integrating AI solutions with existing infrastructure. Collaborates with data science, software engineering, and operations teams to improve reliability, scalability, performance, and operational efficiency.

Owns Sensata’s commercial AI product portfolio across sales, revenue operations, pricing, marketing, and finance. Maps workflows, identifies pain points, defines product requirements, prioritizes roadmaps, and manages backlogs. Leads pilots through production, user adoption, governance, vendor integration, and value measurement. Builds business cases, tracks revenue and productivity outcomes, and communicates product decisions to senior leaders while partnering with AI engineers, data scientists, IT, Finance, and business stakeholders.

Designs, develops, and deploys scalable data science, machine learning, generative AI, and agentic AI solutions. Translates business needs into secure enterprise architectures, builds and evaluates production models, leads AI initiatives from concept through deployment, and establishes monitoring and performance practices. Collaborates with product, engineering, data, and business stakeholders while providing technical leadership across conversational AI, intelligent agents, retrieval systems, and advanced analytics initiatives.

Leads Oncology commercial analytics and brand strategy insights across inline and pipeline assets. Translates business priorities into analytical plans, oversees patient journey and real-world data modeling, supports precision medicine and biomarker initiatives, and applies statistical, machine learning, and AI methods. Manages 15+ team members and cross-functional insights pods while partnering with global, regional, marketing, clinical, medical affairs, and business development stakeholders. Drives scalable analytics, GenAI experimentation, prioritization, value tracking, and executive decision-making.

Sell SailPoint's IGA identity security SaaS to $5B+ enterprises by engaging C-level stakeholders, managing long sales cycles with POCs/RFPs, collaborating with GSIs and channel partners, developing account and opportunity plans, and meeting quota using Challenger methodology.

Leads end-to-end delivery of complex technical epics and engineering initiatives across multiple teams. Responsibilities include planning, estimation, dependency and risk management, Agile delivery, governance, stakeholder communication, milestone tracking, and executive reporting. The role requires strong software development lifecycle knowledge, engineering delivery experience, and the ability to translate technical issues into business outcomes. Experience with AI, Generative AI, Machine Learning, cloud, data, API, or enterprise-scale initiatives is advantageous.

Gather and define accounts payable and payments requirements across the invoice-to-pay lifecycle. Translate business needs into user stories, process flows, functional specifications, and acceptance criteria. Coordinate with stakeholders, engineering, architecture, QA, and delivery teams on ERP integrations, APIs, workflows, testing, compliance, reconciliation, and payment processing. Support prioritization, product delivery, automation opportunities, and platform modernization initiatives.

Provide advanced technical support for escalated customer issues across email, phone, and chat. Troubleshoot Zebra products, collaborate with engineering and product teams, document resolutions, create knowledge base content, analyze support trends, and improve service processes. Train and mentor junior team members, maintain stakeholder relationships, and stay current with emerging technologies and industry practices.

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.

Leads strategy and execution for pricing, driver matching, and incentive products supporting delivery operations across international markets. Owns product vision, roadmaps, discovery, experimentation, analytics, launch execution, and value realization. Partners with Engineering, Design, Analytics, and business stakeholders to optimize driver experience, delivery performance, and cost per order. Influences technical direction, evaluates AI opportunities, mentors product managers, and addresses local regulatory and market requirements in Canada and Latin America.

Design, clean, analyze, and visualize data using SQL and Python; build Tableau dashboards; apply statistics and basic ML/DS concepts; follow software/data-engineering practices (version control, unit testing, high-performance code); work with structured and unstructured data and cloud environments.

Leads Workday integrations and packaged application implementations, including customization, module implementation, enterprise application integration, and development using Workday Studio, EIB, Core Connector, and Workday Extend. Builds and deploys custom Workday applications, coordinates cross-functional product launches, establishes platform best practices, and supports adoption. Applies expertise in HR, payroll, and compensation while exploring AI, machine learning, and intelligent automation capabilities.