Founding Member of Technical Staff - ML Engineering / ...

Who is Recruiting from Scratch: Recruiting from Scratch is a talent firm that focuses on placing the best candidate for our clients. Our team is 100% remote and we work with teams across North America, South America, and Europe to help them hire.Range: $180,000-$250,000 base plus 0% - 1% equity.Our client is looking for a Founding Member of Technical Staff with a background in ML engineering or research.Why not "engineer" or "researcher"? Our client is not going to make a distinction between engineers and researchers to encourage people to have cross-functional scope and impact. Our clients' CTO has a PhD in reinforcement learning but also writes infrastructure code in Rust.Today our client particularly need help building delightful interfaces, but expect everyone to contribute to the entire project over time. The vast majority of your work will be open source. You'll have an opportunity to continue to master your current skills with the flexibility to learn new ones from scratch.You can learn more about our clients' technical roadmap and vision here. As a preview, if you joined today, you'd likely work on advanced inference strategies (e.g. MCTS) or new optimization recipes (e.g. different sorts of RL and APE).Role responsibilities:Build ways to optimize prompts, models, inference strategies, and moreBuild benchmarks and methodologies for offline evaluation and online experimentationCandidate requirements:Able to work in-person with the team 5 daysweek in NYC.Experience tackling hard technical problems, comfortable driving large projects from 0-1.0+ years of experience Frontier work in LLMs or reinforcement learning (either in industry or academia). Broadly looking for seniorstaff SWE or PhD grads, but open to exceptional junior candidates (even top 1% fresh grads).Nice-to-haves:Published researchExperience at frontier labs (e.g. OpenAI, Anthropic, Meta FAIR, Google DeepmindBrain)Major contributions to foundational OSS projects related to LLMs (e.g. vLLM)Top PhD (e.g. Stanford, MIT, CMU, Berkeley)

Created: 2025-02-27