ML Infrastructure Engineer
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
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
Qualifications
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
Bonus
Contributions to ML infra projects or serving frameworks
Knowledge of model optimization techniques (quantization, pruning)
What makes us interesting
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
What we do
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
The Details
Full-time, onsite role in Menlo Park
Startup hours apply
Generous salary, with additional benefits to be discussed during the hiring process
Average salary estimate
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