Research Engineer - ML Infrastructure
Join Chai Discovery as a Research Engineer to optimize ML infrastructure for drug discovery in a fast-paced, innovative environment.
Posted by employer 2 days ago
First seen on Joblaze 16 hours ago
Last verified on the company career page 16 hours ago
What you'll build
- Develop core frameworks for model training and evaluation
- Build training stack across model, layer, and kernel levels
- Profile end-to-end training runs on large GPU clusters
- Ensure new model architectures scale efficiently
- Make ML training stack reliable
Must have
- Strong software system design skills
- Proficiency in Python
- Fluency in Pytorch or JAX
Nice to have
- Deep industry experience with AI/ML teams
- Experience with model training and evaluation
AI in the day-to-day
Chai's models are moving beyond protein structure prediction into real-world therapeutic engineering.
Not disclosed in this posting: compensation, years of experience, visa sponsorship.
Joblaze summary
In this role, the Research Engineer focuses on enhancing the performance and reliability of machine learning models by developing core frameworks for training and evaluation. Key skills include expertise in Python and frameworks like PyTorch or JAX, along with a strong background in software system design and experience with large GPU clusters. This position is well-suited for professionals with significant industry experience in AI/ML, particularly those who have made impactful contributions to complex systems. Chai Discovery emphasizes a culture of high velocity and ownership, fostering collaboration among a dedicated team.
Joblaze insights
Quick facts
- Is the Research Engineer - ML Infrastructure role remote?
- No — this is an on-site role in San Francisco, United States.
- Where is the role based?
- Chai Discovery is hiring for this position in San Francisco, United States.
- What's the tech stack?
- Joblaze extracted these technologies from the posting: JAX, PyTorch, Python.
- What seniority level is this role?
- Chai Discovery targets mid-level candidates for this position.
- Is this full-time or contract?
- Full-time for this Research Engineer - ML Infrastructure role at Chai Discovery.
From the original posting
About the role
Make our models performant, resource efficient and reliable at scale by developing the core frameworks for model training and evaluation, in close partnerships with fellow researchers and engineers.
Build our training stack across model, layer, and kernel levels; optimize workloads through parallelism, quantization, and custom kernels.
Profile end-to-end training runs on large GPU clusters; eliminate bottlenecks and failures; monitor throughput, utilization, and uptime.
Ensure new model architectures and training recipes scale efficiently, from early experiments to frontier-scale runs.
Make our ML training stack maximally reliable: fault tolerance, checkpointing, and deterministic orchestration for long-running, large-scale jobs.
Chai's models are moving beyond protein structure prediction into real-world therapeutic engineering. This is a chance to push the frontier of AI drug design, working alongside a rigorous and craft-obsessed team.
About you
Ideal backgrounds include deep industry experience working with top AI/ML teams on the kinds of problems and systems we describe above—with strong software system design skills, proficiency in Python, and Pytorch or JAX fluency. We look for technical spikes where you have gone deep and demonstrated exceptional impact on real-world problems and systems.
Standard company text repeated across Chai Discovery's postings is omitted here.