About the RoleWe are looking for exceptional engineers to join our team.
You, alongside our team, will own the platform that runs our benchmarks. This spans everything needed to evaluate LLMs at scale: Python libraries, a web platform, distributed systems, cloud infrastructure, and tooling. You'll work across the stack-whatever needs to be built to run benchmarks reliably and efficiently.
At Vals, we believe in autonomy. You will be given a high degree of independence to make decisions on tech stacks, system architecture, and code structure. You will also provide guidance to others on the team, both through informal feedback and formal processes like architecture and code reviews.
Our platform serves startups, enterprises, and research labs measuring model performance. We work with all the major foundation model labs, and some of the largest financial institutions and hospital systems in the world. Our work has been featured by the Wall Street Journal, New York Times, Washington Post, and Bloomberg.
We are building the standard for evaluating the ability of LLMs to perform real-world tasks. You will contribute directly to the infrastructure that makes this possible.
What You'll Do- Build distributed systems to run evaluations across multiple models, benchmarks, and machines at scale
- Deploy cloud infrastructure using IAC, including deployment pipelines, servers, logging, monitoring, etc.
- Contribute to the internal and external libraries we maintain, including our public model library
- Develop full-stack features for our platform using React/TypeScript on the frontend and Python/Django on the backend
- Perform code and architecture reviews for other members of the team
- Help establish engineering best practices across the organization
- Collaborate closely with the research team to ensure our infrastructure meets their needs
RequirementsTechnical
- Strong engineering fundamentals: You can build and ship quickly with high quality. You should have a track record of building things of significant scope (within jobs, side projects, open source, etc.)
- Python expertise: Significant experience in Python, especially in a professional setting.
- System Design Experience: You should be familiar with common concepts like VMs, containerization, load balancers, databases, etc. and when to use them appropriately.
- Familiarity with LLMs: You should have experience working with LLM APIs, and understand concepts like temperature, tokenization, reasoning, etc.
Non-technical:
- Team collaboration: Experience working with development sprints, Git workflows, and pull request reviews.
- Communication: Strong ability to provide and receive feedback effectively. This includes both spoken and written communication (e.g. design docs).
- Comfort with Ambiguity: You will often be the one taking a fuzzy problem and breaking it down into clear and actionable steps.
- Iteration speed: A tenacity to develop and iterate quickly. If you are coming from a large organization, the speed at which we ship might have a learning curve.
- Location: We are an in-person team based in San Francisco. We will support your relocation or transportation as needed.
Nice to Haves- Experience with frontend development, ideally React.
- Experience with Django, FastAPI, or other Python-based HTTP servers
- Experience working with AWS infrastructure, including IaC
- Experience at early-stage startups or your own company
- Interest in AI/ML systems and evaluation
What We Offer- Highly competitive salary and meaningful ownership. Excellence is well rewarded.
- Relocation and transportation support
- Health/dental insurance coverage
- Lunch and dinner provided, free snacks/coffee/drinks
- 401K plan
- Unlimited PTO
- $1,500 housing stipend (within one-mile radius)
