Key Responsibilities at this Role :

- Lead end-to-end development and deployment of scalable ML products in production environments.

- Design real-time and batch ML serving architectures with monitoring and feedback mechanisms.

- Optimize transformer-based models for inference performance, scalability, and production reliability.

- Drive architecture decisions across data pipelines, training infrastructure, and ML platforms.

- Mentor junior ML engineers through code reviews, technical guidance, and design reviews.

- Collaborate with product and engineering teams to align ML outcomes with business impact.

- Own ML initiatives from ideation through deployment, scaling, and continuous improvement.

Must-Haves for this Role :

- 8+ years of hands-on Machine Learning engineering experience.

- Candidate should be currently working as a Principal ML Engineer or Staff ML Engineer.

- Must have built and deployed production-grade Transformer solutions, not just conducted research or model experimentation.

- Hands on experience fine-tuning and optimizing large transformer architectures.

- Strong Python programming with production-grade software development expertise.

- Production exposure to scalable ML deployment and monitoring systems.