Lead the architecture, development, and optimization of Python‑based AI systems, including training pipelines, inference services, and backend components
Build scalable, efficient, and maintainable codebases that support large‑scale machine learning and LLM workloads
Collaborate with ML engineers and researchers to integrate models into production environments
Design and implement APIs, microservices, and internal tools for AI workflows
Optimize model serving performance through batching, caching, quantization, and GPU/accelerator utilization
Oversee data processing pipelines, feature extraction workflows, and distributed computation frameworks
Establish engineering best practices, code quality standards, and technical guidelines for the team
Mentor junior engineers and provide technical leadership across projects
Work with product and platform teams to translate requirements into technical solutions
Ensure systems meet standards for reliability, observability, security, and cost efficiency