What are the responsibilities and job description for the ML Infrastructure Engineer position at Fundamental Research Labs?
About The Role
As our ML Infrastructure Engineer, you’ll build the large-scale systems that power training, inference, and data pipelines for state-of-the-art models. Your work will enable our researchers and ML engineers to train faster, deploy smarter, and iterate without bottlenecks.
If you love building scalable, high-performance systems and want to see your work directly accelerate research breakthroughs, you’ll thrive here.
Responsibilities
As our ML Infrastructure Engineer, you’ll build the large-scale systems that power training, inference, and data pipelines for state-of-the-art models. Your work will enable our researchers and ML engineers to train faster, deploy smarter, and iterate without bottlenecks.
If you love building scalable, high-performance systems and want to see your work directly accelerate research breakthroughs, you’ll thrive here.
Responsibilities
- Design and maintain large-scale distributed training pipelines
- Build and optimize inference infrastructure using vLLM, SGLang
- Implement and scale RL training frameworks for large models
- Architect ML data services pipelines for ingestion, preprocessing, and retrieval
- Optimize cluster utilization across GPUs/TPUs and cloud (AWS, Azure)
- Develop monitoring, benchmarking, and debugging tools for training and inference
- Strong engineering skills in distributed systems and high-performance computing
- Proficiency in Python
- Experience with ML frameworks (PyTorch, JAX) and serving frameworks (vLLM, SGLang)
- Familiarity with RL training infrastructure
- Experience with container orchestration (Kubernetes/EKS) and cloud-native ML workloads
- Contributions to ML infra projects or serving frameworks
- Knowledge of model optimization techniques (quantization, pruning)
- Small, elite team of ex-founders, researchers from top AI Labs, top CS grads, and engineers from top companies
- True ownership You will not be blocked by bureaucracy, shipping meaningful work within weeks rather than months
- Serious momentum We're well-funded by top investors, moving fast, and focused on execution
- Ship consumer products powered by cutting-edge AI research, and
- Build infrastructure that facilitates research and product, and
- Innovate cutting-edge research that will open up new consumer product forms
- Full-time, onsite role in Menlo Park
- Startup hours apply
- Generous salary, with additional benefits to be discussed during the hiring process
