Machine Learning jobs Bangalore

As a Data Science Manager in Bengaluru, you'll lead a team to develop data-driven solutions for the fintech industry. Your role will involve turning data into actionable insights to support business goals.

As an FDE in the technology industry, you'll work on creating, improving, and maintaining software solutions. You'll ensure systems run smoothly and meet user needs in a busy technology environment.

This role will design, build and scale an enterprise-grade AI agent that reasons over workforce data to deliver trusted operational and productivity insights. The successful candidate will own the full AI stack, from agent orchestration and RAG architecture to evaluation frameworks, observability and production reliability.

This role combines advanced data science, machine learning, and software engineering to develop innovative AI-driven solutions. The successful candidate will help deliver predictive models, Generative AI applications, and production-grade software while collaborating across product and engineering teams.

This is a hands-on AI Engineering Lead role responsible for building and leading a team developing agentic AI platforms, intelligence engines, and AI-powered productivity governance products. The position combines technical leadership, architecture ownership, people management, and the opportunity to define how AI-native software is built across the organisation.

• Lead enterprise analytics, AI/ML and automation delivery teams.
• Drive business transformation through data and leadership.

The Lead Research Engineer, Applied ML role is a senior technical leadership position responsible for owning end-to-end machine learning and LLM workstreams focused on oncology clinical data and healthcare AI applications. The role combines hands-on ML development, architectural leadership, mentoring, and cross-functional collaboration to deliver production-grade AI systems at scale.

Looking for a Data Science Tech Lead to lead analytics-driven operational decision-making at the intersection of data science, business analytics, and operations management.

This role combines strategic leadership, stakeholder management, team development, and analytical problem-solving to drive measurable business outcomes.

This role as a Senior AI Engineer in the Financial Services industry focuses on developing and implementing advanced AI models to enhance business analytics and decision-making. Based in Bangalore, the position requires expertise in AI technologies to deliver innovative solutions for financial consultancy challenges.

This role focuses on building production‑grade applied AI systems, including LLM applications, RAG pipelines, and AI agents. You will work across data, reasoning, and backend systems to deliver personalized learning experiences at scale.

The Principal Data Scientist will design, build, and optimize advanced NLP, computer vision, and LLM‑powered systems that automate permitting and regulatory workflows for a leading GovTech platform. The role combines deep technical ownership with strategic leadership, driving AI innovation that directly shapes product direction and government efficiency at scale.

The Senior Data Scientist will own end‑to‑end development of machine learning models that power their cutting‑edge, human‑like voice AI used across major BFSI enterprises. The role involves building scalable NLP and speech intelligence systems, optimizing real-time conversational performance, and driving innovation in a fast‑paced, high‑ownership startup environment.

Build predictive analytics and machine learning solutions to improve customer growth, retention, and lifetime value.

Partner with business leaders to deliver actionable insights and drive data-led decision making.

Drive customer analytics through advanced machine learning.

Build predictive models to improve growth and retention

The AI Tech Lead will deliver intelligent systems from architecture to production at scale. They should be skilled in designing robust AI platforms, data pipelines, and MLOps frameworks, with strong focus on scalability, reliability, and performance optimization. They should also have experience in applying advanced techniques across machine learning, deep learning, NLP, and GenAI (including RAG and LLM-based systems), while embedding responsible AI practices.