Top Machine Learning Jobs in Pune

Own end-to-end machine learning for ecommerce discovery, including recommendation and ranking models, low-latency Python serving, batch pipelines, A/B testing, and production deployments. Operate containerized services on Kubernetes, monitor systems, and extend LLM-powered shopping and catalog applications. The role requires strong recommender systems, search ranking, embeddings, vector databases, streaming, and production ML experience.

Advise clients on developing and implementing data governance strategies. Design policies, frameworks, and practices for data quality, privacy, metadata management, and security. Deliver governance projects, build capability with frameworks and accelerators, and promote governance awareness across stakeholders and committees.

Design and implement a unified orchestration layer coordinating vendor and internal LLMs and human agents. Build production-grade Python services, drive ML projects from design to delivery, ensure secure, scalable AI-enabled customer experiences, and collaborate across teams to meet security, compliance, and performance standards.

Develop, train, deploy, and maintain machine learning and generative AI solutions, including predictive models, NLP applications, chatbots, LLMs, and agentic AI systems. Design scalable ETL pipelines, optimize databases, process large datasets with Spark and Snowflake, and create business visualizations. The role requires expertise across Python, SQL, cloud AI platforms, machine learning frameworks, databases, and data engineering.

Manage strategic enterprise customer relationships, serving as the primary contact for technical support, training, issue resolution, and executive engagement. Partner with sales on account health, growth, and presales activities while advocating for customer needs internally. Apply data analytics, visualization, AI tools, and automation to improve reporting, insights, troubleshooting, and customer value. Support connectivity-focused products and regularly meet clients and attend company functions.

Provide mid-level technical support by troubleshooting and resolving customer issues, managing support tickets to meet SLAs, collaborating with cross-functional teams, improving support processes, and delivering training to junior staff. Support multiple Zebra products and use AI-driven tools to diagnose and resolve problems.

Build and support production MLOps pipelines on GCP using Vertex AI, Airflow, Kubeflow, and related tools. Responsibilities include feature engineering, model deployment, monitoring, retraining, lifecycle management, performance optimization, CI/CD, documentation, and operational support. The role collaborates with data science, data engineering, cloud platform, and MLOps teams to deliver scalable machine learning solutions and establish reusable MLOps standards and best practices.

Design and build scalable data and AI infrastructure for production LLM applications. Responsibilities include developing RAG systems, embedding and vector retrieval pipelines, AI agents, LLM evaluation and observability frameworks, and batch or streaming data platforms using Databricks, Spark, Snowflake, Delta Lake, and Airflow. The role also involves optimizing distributed workloads, establishing data governance and quality practices, and partnering with engineering and product teams to productionize AI capabilities.

Develop and optimize deep learning, graph, and ML techniques for GPU architectures; work with customers to deliver AI solutions; collaborate with architecture, research, libraries, and system software teams.

Drive enterprise sales growth for Akamai Cloud Infrastructure Services by developing new accounts, building strategic account plans, advising executive stakeholders, and identifying cloud, compute, and AI workload opportunities. Lead consultative cross-selling and upselling, manage complex infrastructure deals, forecast pipelines, negotiate contracts, and coordinate enterprise sales teams and technical specialists through close and adoption.

Evaluate and author high-quality computer science content to improve AI model reasoning and accuracy. Analyze complex CS problems, create scenarios/datasets, review AI outputs for correctness, and collaborate remotely to refine guidelines and documentation.

Lead end-to-end AI solutions for clients, manage project delivery and people, partner with sales for business development, collaborate with engineering/MLOps/DevOps, ensure data quality, model training, tuning, deployment, monitoring, and provide executive updates on status and risks.

Build enterprise AI agents using Microsoft Copilot Studio and Azure AI Foundry. Develop topics, triggers, routing, fallback handling, generative answers, RAG, knowledge grounding, citations, metadata-based retrieval, multilingual capabilities, and prompts. Integrate agents with Power Automate, SharePoint, Dataverse, Teams, Azure AI Search, and Azure OpenAI or Foundry models. Support troubleshooting, security, environments, ALM, and DEV/UAT/PROD deployments.

Design, build, and maintain data pipelines, data warehouses and lakes; implement data processing and analysis algorithms; collaborate with data scientists to deploy ML models; lead performance engineering, system stability and scalability efforts; partner with cross-functional teams and ensure compliance with controls and service-level expectations.

Design, prototype, and deliver agentic AI solutions using ML and generative models. Partner with product, engineering, and delivery teams to build, evaluate, and deploy LLM-based solutions, run experiments and POCs, and communicate technical recommendations to stakeholders.

Evaluate AI-generated technical content, craft and answer advanced ML/AI prompts, assess model responses for accuracy, relevance, and clarity, identify errors or hallucinations, and provide feedback to improve AI systems.

Lead the product strategy and execution for an AI-first Email Marketing platform. Own Email Builder UX, AI-native content generation, Sequence AI, delivery/automation, experimentation, reporting, consent management, and cross-functional alignment to drive adoption, engagement, and revenue.

Own end-to-end enterprise sales across Southeast Asia: prospecting, partner-led growth, channel management, demos, negotiation, forecasting, and closing. Build territory and partner plans, hit revenue quotas, represent CloudSEK to CISOs, collaborate with engineering, marketing and customer success, and manage onboarding and contract negotiations.

We are seeking a Director/VP of Sales for the USA market to develop sales strategies, lead a team, drive revenue, and build customer relationships in the cybersecurity sector.

Design and maintain enterprise IT and data architecture focused on data governance, MDM, metadata/catalog, and data quality. Lead technical design, implement MDM and metadata solutions, enable AI-driven automation, collaborate with stakeholders, mentor architects, and recommend technologies to improve data discoverability, reliability, and business value.

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.

The Senior Product Manager will drive product strategy and development, collaborating with cross-functional teams to enhance customer experience, focusing on AI and SaaS solutions.

Own the production lifecycle for traditional ML and generative AI systems, including deployment pipelines, model registries, monitoring, retraining, governance, and incident response. Build reliable AWS-based infrastructure for LLM and agentic applications, establish observability and cost controls, and create operational standards, runbooks, and documentation. Partner with U.S.-based Data Science, Data Engineering, and Product teams while independently managing production workloads during India operating hours.

Lead backend architecture and engineering: design scalable APIs and services, mentor engineers, write complex code, enforce best practices for databases, testing, observability, and integrate ML/LLM workloads.

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.