The company is looking to solve the problem of predicting job performance more accurately than human interviews using AI systems, and is seeking a Software Engineer to scale the infrastructure and systems that power AI-driven hiring.
Requirements
- Strong fundamentals in statistics, SQL, and Python
- Knowledge of experiment design, causal inference, and data modeling
- Strong SQL and Python for analysis
- Nice-to-haves: experience with dbt, dashboarding tools (Hex, Mode, Looker), marketplace/recommendation metrics, or LLM/agent evaluation
- Experience with LLM evaluation, retrieval, and ranking
- Familiarity with data-driven decision making
- Ability to work with large language models (LLMs)
Responsibilities
- Design and build backend systems that support massive scale across hiring and AI evaluation platforms
- Ship critical features across infrastructure, product, and AI-driven systems
- Define north-star metrics for ranking, analytics, and payouts while ensuring measurable improvements
- Design and run experiments (A/B tests and quasi-experiments) and translate insights into product decisions quickly
- Develop dashboards and lightweight models to empower teams with self-service analytics
- Collaborate with engineers and product teams to improve data quality, instrumentation, and system latency
- Prototype quick models (baselines, gradient boosting) to enhance matching and scoring systems
Other
- 0–2 years of experience in data science, analytics, or a similar technical role
- BS/BA in a quantitative field (Computer Science, Applied Math, Statistics, or related) or equivalent work experience
- Ability to communicate clearly with engineers, PMs, and leadership, turning analysis into actionable outcomes
- Curiosity about LLM evaluation, retrieval, and ranking and eagerness to grow alongside colleagues
- Relocation Bonus: $20K (for Bay Area moves)
