Lead Machine Learning Engineer

Job Summary

You'll join our Machine Learning and Data Science experts within the Applied Tech AI team. This team is part of Bain's digital capabilities practice, which includes experts in analytics, engineering, product management, and design. In this multidisciplinary environment, you'll leverage deep technical expertise with business acumen to help clients tackle their most transformative challenges. You'll work on integrated teams alongside our general consultants and clients to develop data-driven strategies and innovative solutions. Together, we create human-centric solutions that harness the power of data and artificial intelligence to drive competitive advantage for our clients. Our collaborative and supportive work environment fosters creativity and continuous learning, enabling us to consistently deliver exceptional results.

Where you'll fit within the team

As a Lead Machine Learning Engineer, you'll help drive innovation by integrating AI and data-driven solutions into strategy and execution. Whether launching new ventures, reimagining user experiences, or building tech-enabled products, you'll work at the intersection of analytics and impact - turning bold strategies into breakthrough results. Bain offers comprehensive benefits and flexible policies that are designed to support you, so you can thrive personally and professionally.

What you'll do

• Design, build, and deliver statistical/ML models and agentic AI/LLM solutions to solve high-impact client problems.
• Architect and implement production-grade ML systems by building enterprise-grade services, applying MLOps and CI/CD for reliable deployment and monitoring, and ensuring high standards in engineering quality and documentation.
• Partner with general consulting teams and client stakeholders to translate business problems into ML solutions, prioritize work, and enable enterprise-scale AI transformation.
• Continuously research emerging frameworks and state-of-the-art AI (e.g., LLMs, agents, retrieval, post-training, etc.) and convert learnings into reusable frameworks, components, and accelerators used across industries and functions.
• Share knowledge and mentor others on best practices tools, and approaches in applied machine learning and AI engineering.
• Contribute to internal RD and learning initiatives to advance Bain's AI capabilities and foster continuous innovation between projects.

Qualifications

• 5+ years of relevant experience or an advanced degree
• Strong theoretical and practical experience in machine learning
• Proficiency in Python, with solid software engineering foundations - including clean code practices, testing, version control.
• Experience with data wrangling, data analysis and modeling using Python, SQL, PySpark or similar tools
• Experience with cloud platforms (e.g., AWS, GCP, Azure) and deploying ML/AI applications.
• Comprehensive understanding of the ML lifecycle, from experimentation and model development to deployment.
• Experience productionizing and exposing ML models (e.g., using FastAPI, Flask, or similar frameworks) for seamless integration into applications and platforms.
• Excellent communicator and collaborator, able to align with technical and business stakeholders in a fast-paced, cross-functional environment.
• Curious and growth-oriented, passionate about exploring new tools, mentoring peers, and sharing best practices.
• Adaptable and self-driven, comfortable operating with autonomy, embracing feedback, and learning new skills to deliver client impact.
• Location: New Delhi, Bengaluru, Mumbai (Hybrid)
• Travel is required. This position requires regional travel. Travel frequency and destinations will vary based on project needs.

Nice to Have

• Experience with RD or academic research
• Interest in publishing technical content and mentoring others

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.