Top Tech Jobs & Startup Jobs in Mumbai

Supports enterprise transformation initiatives through change management planning, impact and readiness assessments, stakeholder engagement, reporting, and adoption activities. Develops change narratives, stakeholder analyses, change plans, and supporting resources while coordinating with project teams, communications, learning, and business leaders. Tracks change impacts, risks, feedback, and lessons learned to improve methodologies and sustain effective adoption.

Develop and deploy machine learning, deep learning, and agentic AI systems for business and R&D challenges. Responsibilities include building AI agents with LLMs, RAG, memory, tools, and orchestration; leading end-to-end data science projects; creating predictive models and analytical solutions; developing scalable MLOps pipelines; deploying and monitoring production models; and communicating insights to clients.

Supports logistics planning and execution across external manufacturing sites and warehouses. Resolves escalations, monitors production and order sequencing, manages SAP factory calendars and downtime plans, coordinates EDI integrations, and supports site start-ups, transitions, and exits. Trains and coaches sites on planning systems and business processes while leading process improvements and collaborating with manufacturing, logistics, technical, and supply chain teams.

Drives sales growth for Walmart and club-channel customers through syndicated data analysis, sales reporting, trade planning, digital insights, and market performance evaluation. Maintains automated reporting, supports sales planning, identifies business opportunities, and recommends execution improvements. Manages multiple projects, ensures data quality, mentors team members, and builds stakeholder relationships through clear presentations and influential communication.

Leads AI and machine learning strategy, model development, technical explorations, and production deployment. Uses Vertex AI and MLOps practices to deliver scalable solutions, collaborates with business and engineering stakeholders, oversees the AI development lifecycle, manages model performance, mentors data scientists, and promotes AI literacy. Requires expertise in supervised learning, optimization, Python, SQL, GCP, and AI solution architecture.

Manage day-to-day contingent workforce program operations for India-based engagements. Serve as the operational subject matter expert, monitor KPIs and SLAs, ensure labor-law and policy compliance, resolve issues, support vendors and resource managers, analyze performance and cost savings, and recommend process improvements.

Leads the design and implementation of scalable MLOps pipelines on GCP using Vertex AI, Kubeflow, Airflow, and MLflow. Automates model deployment, monitoring, retraining, logging, and orchestration while establishing CI/CD, quality, and architecture standards. Provides production support, troubleshooting, optimization, and root cause analysis; partners with data science, engineering, and business teams; researches emerging technologies; and mentors engineers.

Leads FP&A and financial governance for global supply chain raw materials. Partners with sourcing, procurement, operations, and finance teams on planning, forecasting, reporting, margin improvement, cost savings, and financial analysis. Uses SAP cost modules to assess pricing, volume, incoterms, and vendor impacts, identify variances and root causes, improve reporting processes, and provide data-driven insights to business leaders.

Processes customer promotional invoices, manages accounts receivable and delinquent accounts, reconciles inventory and transactional grain accounting, supports product costing and SAP master data, coordinates exports and customs documentation, and ensures SOX compliance, accurate month-end invoicing, audit readiness, stakeholder collaboration, and continuous process improvement.

Designs, builds, and supports cloud data engineering, ETL, SQL, and data warehouse solutions primarily on GCP. The role integrates enterprise data, supports platforms and scheduling tools, partners with technical and business stakeholders, leads small projects, drives automation and continuous improvement, and trains team members. Required expertise includes Python, SQL, BigQuery, Composer, Cloud Functions, dbt, cloud storage, data warehousing, and data governance.