About the role
- Tackle open-ended AI problems: clarify goals, propose approach options, and choose sensible trade-offs.
- Stand up end-to-end workflows—from data wrangling and evaluation through deployment and monitoring.
- Build quick experiments and MVPs to de-risk unknowns, then harden them for production.
- Create lightweight tooling that helps others explore, test, and iterate on AI features.
- Work across teams (security, infra, product, domain experts) to ship responsibly in real-world environments, including sensitive contexts.
- Document decisions, assumptions, and risks so others can build on your work.
Requirements
- U.S. citizenship.
- Solid software fundamentals and strong Python skills; you write clear, maintainable code and tests.
- 2–5 years of hands-on experience building and shipping ML/AI or NLP-driven features (titles less important than impact).
- A generalist mindset: you can learn unfamiliar libraries, models, or stacks quickly and pick the right level of sophistication for the problem.
- Practical evaluation chops: you design metrics, create test sets, and know when something is “good enough” to pilot vs. needs more rigor.
- Data instincts: you’re comfortable sourcing, cleaning, labeling, and shaping both structured and unstructured data.
- Bias for action and ownership in fast-moving, resource-constrained settings.
- Thoughtful approach to safety, privacy, and policy constraints.
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
Pythonmachine learningartificial intelligencenatural language processingdata wranglingMVP developmentmetrics designdata cleaningdata labelingdata shaping
Soft skills
problem-solvingcollaborationdocumentationadaptabilityownershipbias for actionthoughtfulnessevaluationcommunicationgeneralist mindset