Senior Machine Learning Engineer

End-to-End ML Development: Architect, train, evaluate, and deploy machine learning models (both predictive and generative) into scalable production environments.

• MLOps & Infrastructure: Design and maintain robust ML pipelines, ensuring seamless model monitoring, versioning, automated testing, and CI/CD integration.

• Collaboration & Leadership: Partner with Data Engineers, Product Managers, and Backend Engineers to translate business requirements into technical AI solutions.

• Mentorship: Act as a technical multiplier by mentoring junior engineers, conducting code/model reviews, and championing engineering best practices.

• Innovation & Research: Stay current with the rapidly evolving AI landscape (e.g., LLMs, Agentic workflows, new architectures) and prototype state-of-the-art solutions for existing bottlenecks.

• Optimization: Fine-tune and optimize models for inference latency, throughput, and cost-efficiency at scale.