Top Machine Learning Jobs in India

Design, build, and operationalize a unified AI/ML data collection platform. Responsibilities include LLM/RAG pipelines, data ingestion, feature management, model lifecycle and deployment, observability, scalable distributed systems, and mentoring engineers to deliver production-ready ML solutions.

Lead design and delivery of conversational AI and voice solutions (Dialogflow) across platforms (Genesys, AWS Connect). Build/optimize voice bots, LLM-based capabilities (Gemini Enterprise CX), real-time streaming with LiveKit, integrate AI with backend systems, establish scalable architectures and MLOps, and lead technical teams to improve customer experiences.

Design, build, and deploy generative AI applications and traditional ML models. Implement RAG, embeddings, vector search, prompt engineering, fine-tuning, and scalable services integrating third-party AI APIs. Establish model evaluation, monitoring, CI/CD, and guardrails. Collaborate with product, data, and engineering teams to productionize ML features and ensure reliability and low-latency performance.

Build data infrastructure and reliable pipelines, analyze product usage, train traditional and LLM-based models, define product metrics, run experiments, and translate findings into product and go-to-market decisions. The role combines data science, data engineering, product analytics, machine learning, and stakeholder communication, with ownership across data modeling, evaluation, experimentation, and product insight generation.

Lead and grow an engineering team responsible for Wi-Fi optimization, device management, provisioning, lifecycle, and cloud connectivity control systems. Own the roadmap, architecture, delivery, reliability, hiring, coaching, and performance of 8–12 engineers. Drive cross-functional execution, customer escalations, standards strategy, design reviews, coding, and large-scale operational decisions across embedded, cloud, and networking systems serving tens of millions of devices.

Develop and maintain machine learning models, statistical tools, predictive analytics, segmentation, and document classification solutions for mortgage operations. Translate business needs into modeling tasks, build experiments, support data pipelines and model deployment, and monitor model performance. Apply supervised learning, clustering, NLP, and automation techniques while maintaining documentation and audit readiness. Collaborate with Product, Engineering, Analytics, and senior data science teams in a regulated financial environment.

Build and maintain predictive and analytical models supporting mortgage marketing, origination, and servicing decisions. Conduct marketing experiments, analyze campaign performance, develop SQL and ETL workflows, build and validate campaign files, automate recurring processes, and translate business questions into actionable insights. The role partners with marketing and business teams while ensuring accurate, governed, execution-ready analytical outputs.

The Tech Project Manager will define and execute the vision for generative AI products, manage cross-functional teams, and oversee project lifecycles to enhance competitiveness and user experience.

As a Data Scientist, you will enhance data productivity, develop models, collaborate with business stakeholders, and provide insights to improve product usability and reseller performance.

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.

The role involves providing advisory services in Third Party Risk Management (TPRM) leveraging AI and Machine Learning skills with a strong foundation in Python.

The Senior Manager will lead the Data Science and Generative AI team, defining the AI strategy and overseeing the development of AI solutions while mentoring staff and ensuring best practices in AI governance.

The Senior Machine Learning Engineer will lead the development of a GenAI platform, enhance AI infrastructure, mentor junior engineers, and drive project ownership in a startup environment.

Analyze data to identify trends and insights, and develop predictive models using machine learning for forecasting and classification.

Identify and engage EHS/Sustainability subscribers, deliver product demos, manage the sales lifecycle to close new subscriptions, build customer relationships, and provide product/process feedback while staying current on industry trends and digital innovations.

Lead monthly close for multiple regional entities, manage P&L, prepare and present monthly financial reports, ensure statutory compliance (GST reconciliation, TDS filing), support internal and external audits with schedules and PBCs, maintain confidentiality, and implement AI-driven process improvements.

The Director of Strategic M&A Integration & Value Realisation will lead the integration process of global mergers and acquisitions, focusing on organizational and cultural integration, cost discipline, and value realisation across the company.

Lead product marketing for InMobi's Microsoft Ads representation business globally. Own GTM strategy, sales enablement, and client solution frameworks; produce content and presentations; collaborate with sales, centralized marketing, Microsoft stakeholders, and regional teams to drive revenue and market share.

Lead JustCall's product function: set vision and strategy, align cross-functional teams, ship AI-powered communication and revenue solutions, grow a high-performing PM organization, and drive measurable retention, engagement, and revenue outcomes.

Use data and advanced analytics to solve complex business problems, design and deploy scalable ML/data products on cloud platforms, collaborate with clients and cross-functional teams, and communicate actionable insights.

Manage full-cycle recruitment for technical roles, partner with hiring managers, and develop sourcing strategies to attract top talent in AI and data-centric fields.

Lead AI initiatives, craft product vision, manage lifecycle, utilize data for decisions, and foster collaboration across teams.

The Senior Vice President, Full-Stack Developer leads development and delivery of key features, mentors staff, influences architecture, and drives modernization initiatives across platforms using diverse technologies.

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.

The Customer Success Business Partner at Lyric drives customer adoption and retention for strategic accounts, leveraging expertise in AI and supply chain operations.