Senior Research Engineer Machine Learning, AI for Science
Core
Architect, design, and implement large-scale data pipelines and distributed systems for machine learning training, evaluation, and benchmarking of heterogeneous scientific data.
Role type
Senior IC machine learning infrastructure engineer (AI for Science)
Builds
Scalable ML training infrastructure, data pipelines, and agentic workflows for scientific model development
Domain
AI for Science, Large-scale Data Processing, Distributed Systems
Deliverable
infrastructure
Required skills
Python, PyTorch, Jax, Distributed Systems, GPU/Tensor Accelerator Optimization, Cloud Platforms, HPC, High-Performance Scientific Software, Agentic Frameworks, Orchestration Systems
Preferred skills
Experience with major cloud platforms, Experience with HPC, Experience developing high-performance scientific software
Technologies
Python, PyTorch, Jax, Cloud Platforms, HPC, GPUs
Responsibilities
Develop and maintain efficient, reliable, and scalable infrastructure for large-scale machine learning training, evaluation, and benchmarking. Architect, design, and implement large-scale data pipelines for heterogeneous scientific data. Build and optimize distributed data processing, model training, evaluation, and benchmarking pipelines. Develop software and agentic workflows to automate and improve model development, training, evaluation, and benchmarking. Continuous monitoring and improvement of the stability of data, training, evaluation and benchmarking workflows.
Seniority
Senior, hands-on IC
