Machine Learning Engineer (AI)

TL;DR

Machine Learning Engineer (AI): Design, build, and deploy end-to-end ML systems in production with an accent on ranking, retrieval, NLP, personalization, and prediction. Focus on owning the full ML lifecycle, creating robust evaluation frameworks, and improving experimentation tooling for scalable systems.

Location: San Francisco, CA

Salary: $190k - $290k dependent on experience plus equity

Company

High-growth, Series A AI-powered hiring marketplace backed by leading Silicon Valley investors and iconic tech founders.

What you will do

• Design, build, and deploy end-to-end ML systems in production.
• Develop and optimize models for ranking, retrieval, NLP, personalization, and prediction.
• Own the full ML lifecycle: data, features, training, evaluation, deployment, and monitoring.
• Create robust evaluation frameworks to measure performance, bias, reliability, and business impact.
• Partner cross-functionally to ship high-impact features quickly.
• Improve experimentation, tracking, and observability tooling and establish best practices for scalable ML systems.

Requirements

• 5+ years building and shipping production ML systems.
• Strong Python skills and experience with ML libraries (e.g., scikit-learn, XGBoost, LightGBM, PyTorch).
• Experience with large-scale data, feature pipelines, and deployment.
• Solid understanding of evaluation, experimentation, and performance trade-offs.
• Comfortable across traditional ML and modern LLM systems.
• Strong product sense, prioritization skills, and collaborative communication.

Nice to have

• Experience with LLMs, RAG, ranking, or personalization.

Culture & Benefits

• Salary of $190k - $290k dependent on experience plus meaningful equity.
• Opportunity to own and ship impactful ML systems end-to-end.
• Fast-paced, high-ownership environment where your work directly influences company outcomes.
• Comprehensive health benefits, flexible time off policy.
• Team off-sites and a strong in-person culture.