Demonstrated ability to use LLMs to write software and build complex systems.
Hands-on experience with self-hosting and evaluating open-source models.
Proficient in Python and capable of managing complex technical systems end-to-end.
Able to navigate unfamiliar codebases and contribute in various domains.
Strong grasp of engineering fundamentals like version control, testing, and reproducibility.
Responsibilities
Utilize LLMs and coding agents to create software and intricate systems, advancing internal agentic technologies.
Self-host and assess open-source models, developing tools that ensure agent reliability within workflows.
Engage agents in addressing open-ended scientific inquiries through research, experimentation, and analysis.
Contribute to diverse maintenance and research initiatives, adapting as project priorities evolve.
Maintain the health and functionality of cloud infrastructure and development environments.
Benefits
Highly competitive compensation package.
Visa sponsorship available for qualified candidates.
Full Job Description
The role
You'll be a generalist research engineer, moving fluidly across our maintenance and research projects wherever leverage is highest. The through-line is using LLMs and agents to build software and complex systems - including for open-ended scientific questions, not just engineering ones. You'll have real latitude to decide what to build and how, and your work will land directly on how fast our researchers move and what our science can do.
What you'll do
Use LLMs and coding agents to build software and complex systems, and keep advancing the internal agentic systems we use to write our code and maintain our infrastructure
Self-host and evaluate open-source models, and write the harnesses, tooling, and scaffolding that make agents reliable for our workflows
Apply agents to scientific questions - an open-ended remit spanning genuine research, experimentation, and analysis, not only software development
Contribute across a variety of maintenance and research projects as priorities shift, from internal tooling to data and model work
Keep our cloud infrastructure and development environments healthy
Essential experience
Demonstrated ability to use LLMs to write software and build complex systems
Hands-on experience with open-source models: self-hosting, evaluation, and writing harnesses or scaffolding around them
Strong Python and the ability to own complex technical systems end to end
Comfort working across an unfamiliar codebase and shipping in areas outside your prior expertise
Sound engineering fundamentals: version control workflows, testing, and reproducible environments
Highly preferred
Background in biology, chemistry, or a related scientific domain
Scientific computing or ML/research-tooling experience
Substantial professional software engineering experience
Experience building or operating agentic systems (multi-step tool use, orchestration, evaluation harnesses)
Familiarity with cloud infrastructure (AWS or GCP), containerization, and infrastructure-as-code
Logistics
Compensation is highly competitive. We're also able to sponsor visas for the right candidate.
