Machine Learning Engineer
Core
Bridge the gap between cutting-edge ML research and scalable, reliable systems to bring zero-shot discovery models from research to production.
Role type
Machine Learning Engineer (Production & MLOps)
Builds
Scalable, reliable ML systems for zero-shot discovery models
Domain
AI/ML, Model Optimization, MLOps
Deliverable
production ML models
Required skills
PyTorch, deep learning fundamentals, CUDA kernel optimization, model quantization, distributed training, Python, CI/CD
Preferred skills
ONNX, TensorRT, micro-batching, caching strategies
Technologies
PyTorch, ONNX, TensorRT, CUDA, Python
Responsibilities
Deploy and optimize ML models for production serving; Build robust MLOps pipelines for training, evaluation, and deployment; Optimize CUDA kernels and model inference for latency-critical applications; Implement micro-batching, caching, and quantization strategies; Collaborate with researchers to productionize novel architectures.
Seniority
Mid-Senior, hands-on IC