Top Machine Learning Jobs in India

Design, develop, test, deploy, and maintain UiPath RPA bots; capture stakeholder requirements; create process documentation; collaborate with cross-functional teams; support automation lifecycle and SQL integrations.

Validate and test models across credit risk, marketing, fraud, and account management; use GCP to automate workflows; execute AI validation projects; collaborate cross-functionally; contribute to AI/model risk management policies and maintain regulatory best practices.

Entry-level reporting analyst role seeking B.Tech candidates (CS or Data Science). Freshers should have a solid foundation in Python, machine learning, and NLP. Project or internship experience is beneficial.

Lead developer on Global Brokerage team designing, building, testing and deploying high-performance brokerage and data warehouse solutions. Owns system design, ETL/data engineering, SQL optimization, Snowflake implementations, and platform transformation. Acts as technical subject-matter expert, mentors team, and collaborates with business partners to deliver scalable data and analytics solutions.

Support aeroacoustic integration across aircraft design stages by evaluating noise sources and propagation, defining requirements, developing methods and technologies, monitoring noise during development, and collaborating with multidisciplinary teams to meet aircraft noise and performance targets.

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.

Lead end-to-end enterprise AI/GenAI solution architecture and delivery: discovery, design, development, deployment, governance, and mentoring. Engage stakeholders, support pre-sales, define scalable LLM/RAG/agent architectures using vector DBs, cloud, MLOps, and best practices.

Develop advanced machine learning, predictive and optimization models, transform large datasets into actionable insights, design experiments, and produce visualisations and dashboards to influence commercial decisions and drive customer growth and retention.

Design, implement, and optimize scalable AI/ML solutions (including generative AI), train and evaluate models, deploy at scale on cloud/Databricks, build data pipelines, containerize and expose APIs, mentor engineers, and collaborate with cross-functional teams to translate business needs into production AI systems.

Lead design and implementation of scalable ML, deep learning, and generative AI solutions (NLP/LLMs), build production pipelines on cloud, create document-parsing models, collaborate cross-functionally, and publish research and patents.

Lead design, development, and scaling of enterprise AI/ML and generative AI platforms and agentic systems. Build and mentor globally distributed engineering teams, operationalize AI-enabled SDLC (AIDLC), drive productionization, observability, and performance, and align AI initiatives with business outcomes while championing responsible AI governance and cross-functional delivery.

The Senior Software Engineer will design and maintain backend software, APIs, and collaborate with various teams to enhance product offerings and scale services.

The role focuses on evaluating Generative AI solutions, ensuring quality standards, mentoring team members, and improving data models in an academic research setting.

The Senior Business Analyst will optimize order management processes, enhance Oracle Applications, and lead key business initiatives, acting as a liaison between technical teams and stakeholders.

Lead development and innovation of managed switching solutions targeting SMEs, focusing on product features, cost-performance, technical architecture, and market-driven solutions.

This role involves conducting advanced AI research, designing intelligent systems, and developing solutions while ensuring responsible AI practices. The candidate will lead experimentation, implement AI models, and translate AI capabilities into business impact while mentoring junior professionals.

The Staff AI Scientist will conduct advanced AI research, design production-grade systems, mentor staff, and translate AI innovations into business solutions.

Lead vision, strategy, and roadmap for Device Intelligence and Behavioral Biometrics product lines. Drive discovery and delivery with Engineering and Data Science, engage customers to inform product direction, define metrics, and partner with GTM teams for pricing, positioning, and launches across India and international markets.

Lead the Sales Engagement product area: define vision and roadmap, conduct customer discovery, write requirements, partner with engineering/design/data science, ship features, and track success metrics to improve AI-powered revenue intelligence.

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.

The Technology & AI Manager leads technology and AI initiatives, developing roadmaps, implementing solutions, and enhancing operational efficiency through analytics and machine learning.

Drive technical direction and build end-to-end onboarding and adoption experiences across frontend and backend. Design, operate, and optimize REST and GraphQL APIs, integrate data pipelines and ML/AI features, ensure scalability, security, observability, and developer productivity, mentor engineers, and collaborate with cross-functional and distributed teams.

Product Owner for Lloyds Banking Group's Resolving Financial Crime lab. Owns a single product backlog, prioritises work, manages delivery and resources, champions customer outcomes, leads feature-team delivery, and applies domain knowledge in financial crime and ML/AI to drive product success.

Lead and grow an India-based engineering organization to design, build, and operate an AI-driven multi-country SaaS platform. Define technical vision and roadmap, architect scalable multi-region solutions, oversee AI/ML model development and deployment, ensure security/compliance, drive DevOps/CI-CD practices, and collaborate with product, country reps, and compliance teams to deliver localized, production-ready solutions.

Lead design and delivery of enterprise GenAI, LLM, RAG, and Agentic AI solutions. Build scalable ML pipelines, deploy models to production, integrate with frontend/backend systems, ensure responsible AI, monitor model performance, and mentor engineers while partnering with product and data teams.