Machine Learning Platform Engineer
Bjak · Remote · United States ·
COMPENSATION
€•• – ••k
Listed on the employer's job board (Ashby)
- Fully remote
- ML Platform Engineering
- Python + PyTorch
- GPU Infrastructure
- Distributed Systems
You will design and operate the systems behind the AI stack, covering model training, evaluation, deployment, and observability. Working with AI engineers and researchers, you will turn models into reliable, scalable production systems while building tooling that enables rapid experimentation.
What you'll do
- Build and operate ML infrastructure powering AI products
- Design systems for model training, evaluation, and deployment
- Optimize model serving for high-throughput and low-latency workloads
- Develop pipelines for data preparation and continuous model improvement
- Create tooling to help researchers ship models faster
- Build evaluation infrastructure to measure model quality and regressions
- Implement observability, monitoring, and alerting for ML workloads
- Identify bottlenecks and improve system performance across the stack
What you'll need
- Strong software engineering fundamentals and production system experience
- Experience building ML infrastructure or production machine learning systems
- Knowledge of model deployment, inference, evaluation, or data pipelines
- Strong understanding of distributed systems and reliability
- Ability to write clean, maintainable, production-quality code
- Comfortable working in ambiguous, fast-moving environments
- Bias toward ownership, experimentation, and continuous improvement
Stack
- Python
- PyTorch
- JAX
- vLLM
- SGLang
- TensorRT-LLM
- Cloud infrastructure
- Distributed systems
- GPU infrastructure
- Vector databases