Design, build, and maintain scalable, production-grade GenAI services in the cloud
Lead architectural design and guide the development of optimized ML pipelines for cloud-based inference and integration
Drive the bridge between research and product teams throughout the lifecycle—from prototyping to deployment
Optimize model performance, GPU utilization, and service orchestration at scale
Work collaboratively with PMs, TPMs, and engineering leads to build and implement the GenAI roadmap
Define technical direction, conduct building reviews, and establish guidelines for reliability, scalability, and maintainability
Own and improve CI/CD systems and monitoring pipelines for ML services
Mentor engineers across ML and backend fields, encouraging a culture of technical excellence
Provide tier-1 production support, ensuring service SLAs and customer satisfaction

MS or PhD in Computer Science or a related field, or equivalent experience in the industry.
8+ years' experience architecting cloud services and infrastructure for large scale use, reliability and performance
3+ years of experience with GenAI workloads—including fine-tuning and inference at scale
Strong foundation in Transformer architecture, Diffusion models, CLIP, VAE, Encoder/Decoders
Deep understanding of model serving, orchestration, and GPU resource management in distributed environments
Knowledge of model optimization techniques (quantization, pruning, distillation, etc.)
Expert-level coding and debugging skills in Python; familiarity with JavaScript/TypeScript is a plus
Hands-on experience with Kubernetes, Docker, and ML-Ops platforms (e.g., MLflow, KServe, Triton)
Familiarity with CUDA, Torch AOTinductor, and frameworks such as PyTorch, TensorFlow, or ONNX Runtime
Proven track record of leading complex, high-stakes technical initiatives across teams
Strong problem-solving skills and a mentality for developing well-tested, production-quality software
Excellent communication and multi-functional collaboration skills.

Staff Machine Learning Engineer

Key skills