Description :

Role Overview :

We are seeking an experienced Engineering Manager Machine Learning to lead and scale high-performing ML teams while remaining technically hands-on. This role combines people leadership, ML systems expertise, and strategic execution, with a strong focus on delivering production-grade ML and LLM-powered solutions at scale.

Key Responsibilities :

- Lead, manage, and scale ML engineering teams (8+ engineers), driving execution excellence, ownership, and delivery quality.

- Conduct performance reviews, mentorship, coaching, and career development for team members.

- Provide technical leadership across the full ML lifecycle, from model development to production deployment and monitoring.

- Oversee the design, development, and deployment of LLMs and large-scale ML models in production environments.

- Guide and review work on fine-tuning, RLHF, multi-GPU training, and inference optimization.

- Own and evolve ML infrastructure, including distributed training, inference pipelines, and multi-cloud deployments (AWS, GCP, Azure).

- Drive architectural decisions around RAG systems, including vector databases such as FAISS, Pinecone, and Weaviate.

- Partner with Product, Data, and Platform teams to align technical execution with business goals.

- Balance hands-on technical depth with strategic planning, prioritization, and roadmap ownership.

- Ensure engineering best practices, reliability, scalability, and cost efficiency across ML systems.

Required Qualifications :

- 9+ years of overall ML engineering experience, with 2+ years in an engineering management or leadership role.

- Proven experience managing and scaling teams of 8+ engineers, including performance management and career development.

- Strong hands-on experience deploying LLMs or large-scale ML models into production.

- Deep expertise in model fine-tuning, RLHF, distributed/multi-GPU training, and inference optimization.

- Solid background in ML infrastructure and distributed systems, including multi-cloud environments.

- Hands-on experience with vector databases (FAISS, Pinecone, Weaviate) for RAG-based applications.

- Excellent leadership, communication, and stakeholder management skills.

- Strong ability to make strategic decisions while maintaining technical rigor.

Nice to Have :

- Experience scaling ML platforms in high-growth or enterprise environments.

- Exposure to MLOps tooling, monitoring, and cost optimization strategies.

- Prior experience leading cross-functional ML initiatives.