Top Machine Learning Jobs in Pune

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.

Lead complex data science and analytics initiatives from concept through implementation. Develop predictive models, analytical frameworks, dashboards, and decision-support tools using statistical and machine learning techniques. Partner with stakeholders to translate business needs into scalable solutions, oversee data quality and integration, present findings, manage delivery, and mentor technical team members.

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.

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 product operations data and analytics strategy, engineering teams, delivery tooling, reporting, governance, performance measurement, and portfolio planning. Owns AWS data engineering, BI strategy, data architecture, pipelines, dashboards, controls, roadmaps, and stakeholder alignment. Drives operational excellence, scalable reporting, value tracking, risk management, and continuous process improvement while mentoring teams and advising senior leaders.

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.

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.

Designs and deploys industrial automation solutions across manufacturing plants, including PLC, SCADA, HMI, MES, ERP, IIoT, AI, RPA, and cloud integrations. Supports new product introduction, develops automated processes and fixtures, creates data pipelines and dashboards, standardizes solutions across sites, and builds business cases and automation roadmaps to improve safety, quality, throughput, decision-making, and cost efficiency.

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.

Lead Workday integrations, packaged application implementations, custom Workday Extend app development, and cross-functional product launches. Configure Workday Studio, EIB, and Core Connector solutions; manage application lifecycles through production deployment; establish platform best practices; and support adoption through team development. Apply HR, payroll, and compensation domain knowledge while exploring AI, machine learning, and intelligent automation capabilities.

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.

Supports sales-force effectiveness through data cleaning, access governance, KPI reporting, performance trend analysis, and migration from Excel tracking to Power BI dashboards. The role also provides user support, onboarding and training assistance, documentation, process standardization, and continuous improvement across regional sales entities.

Analyzes large datasets to identify trends, correlations, data-quality issues, and actionable business insights. Builds data pipelines, logical data models, interactive dashboards, visual reports, and automated reporting processes. Partners with stakeholders to recommend operational improvements, strengthen controls, and support data-driven decisions. The role also involves data integration, engineering, analytics, machine learning fundamentals, and payments-domain knowledge.

Design and deliver scalable Generative AI solutions using LLMs, RAG, AI agents, vector databases, and multimodal models. Lead cloud, MLOps, security, governance, and architecture strategies across AWS, Azure, and Google Cloud. Translate business needs into technical solutions, support client workshops and pre-sales, present strategies to executives, and mentor data science, ML engineering, and software teams.

Provide production support for critical banking technology infrastructure, rapidly resolve incidents, participate in major incident management, and improve application-support efficiency. The role involves Linux/Unix administration, Java and database technologies, middleware, microservices, containers, cloud platforms, monitoring, scheduling, CI/CD, and messaging tools. Responsibilities also include stakeholder communication, risk and control management, technical issue resolution, operational support during shifts and releases, and occasional weekend coverage.

Leads data science teams supporting commercial healthcare analytics, translating business needs into analytical problems and production-grade ML and GenAI solutions. Responsibilities include defining technical requirements, developing models, applying GenAI, managing end-to-end projects, collaborating with stakeholders, presenting insights to executives, mentoring data scientists, and building expertise in oncology analytics, patient-level data, HCP analytics, and segmentation.

Design and lead scalable Generative AI solutions using LLMs, RAG, AI agents, vector databases, cloud platforms, and MLOps/LLMOps. Translate business needs into secure technical architectures, conduct client workshops, support pre-sales, and present AI strategies to executives. Establish governance, security, monitoring, and compliance frameworks while mentoring data scientists, ML engineers, and software teams. Evaluate emerging technologies, guide implementation approaches, and drive enterprise AI adoption.