- +3
- +2
- New York, New York
About
We are looking for Software Engineering Interns to help develop our reliability platform, with a focus on:
- Data-efficient alignment of evaluation models
- Dynamic testing of AI applications
- Observability and anomaly detection
- Discrete optimization (with applications in architecture search and automated prompting)
Our work is both intellectually stimulating and practically useful. Your work will result in net-new primitives, frameworks, and algorithms for developing robust LLM applications. You work will directly influence how LLM apps are tested, verified, and deployed everywhere.
Annual Salary
$100,000 - $125,000 USD
Responsibilities
- Work directly with customers to adapt our core R&D for different domains.
- Build out core infra, cloud tooling, and UX around our algorithms.
- Ship delightful tools that are used by AI application developers all across the world.
- High-agency, customer-centric full-stack experience, e.g. ex-founder or ex-founding engineer.
- Strong open source presence or strong track record of software engineering projects and employment.
- Experience with ML in an applied setting.
- Can ramp up quickly to understand our research.
- Location policy: In NYC.
- US visa sponsorship: If you are exceptional, we will sponsor.
- Compensation and Benefits: We provide generous salary, equity, and benefits
We're not here to write GPT wrappers or get rich quick off the AI bubble. We're here to solve the hardest problem in AI: making it safe, reliable, and production-ready.
Since our company's inception in 2024, we've amassed amazing customers like OpenAI, Anthropic, AI21, and several others. We've developed best-in-class tooling for evaluation, dynamic testing, red-teaming, observability, and continuous robustification. And we're backed + advised by the founders of Cognition, Hugging Face, Weights and Biases, Nous, Etched, Okta, Replit and C-suite execs from Google, Stripe, Databricks, Robinhood, and more.
Our core team is exceptionally fit for this mission. We turned down Stanford PhDs, got into & rejected Y Combinator, wrote ML-guided matchmaking for 50,000+ students, built an educational nonprofit supporting 60 countries, and did some other cool things along the way. Our early hires include an MIT PhD with 21,000+ Physics/ML/Stats citations, a Datadog engineering manager who led their GenAI observability team, a Citadel quant with a huge open-source presence, and more.
We can only serve our mission with an incredibly high talent-density team. Come here to push yourself, learn fast, experience excellence, grow with each other, and pursue your life's work.
Nice-to-have skills
- UX Design
- Machine Learning
Work experience
- Fullstack
- Data Engineer
- Agile Coach / Scrum Master
Languages
- English