Senior Machine Learning Engineer

San Francisco, CA (Onsite).

$190,000-$300,000 + Equity

I'm working with a rapidly growing AI-powered hiring marketplace that's transforming how companies connect with recruiters and talent.

This is a product ML role. Not research. Not foundation models. Not LLM demos.

You'll be building production systems that directly improve matching quality, ranking relevance, marketplace efficiency, and hiring outcomes. The problems sit at the intersection of recommendations, search, marketplace dynamics, and applied AI.

As one of the earliest ML hires, you'll have significant ownership and influence over both the technical direction and future of the ML function.

You'll work on problems such as:

• Recommendations and ranking: who should be surfaced to whom, in what order, and why

• Marketplace matchmaking across a two-sided network

• Supply and demand optimization, incentives, and feedback loops

• Applied AI systems that automate workflows while maintaining quality and trust

• Evaluation systems that measure relevance, quality, and business impact

We're looking for engineers who have:

• Built and shipped recommendation, ranking, matching, or personalization systems in production

• Owned ML systems end-to-end, from experimentation and model development through deployment and iteration

• Experience measuring model performance through offline evaluation and online experimentation

• Strong software engineering fundamentals and experience productionizing ML systems

• A track record of improving measurable product or business outcomes through machine learning.

Particularly relevant experience includes:

• Search ranking and relevance

• Recommendation systems

• Marketplace matching systems

• Personalization and decision systems

• Ads ranking or feed ranking

• Experimentation platforms and A/B testing

If you're excited by recommendation systems, ranking, matching, and solving real-world marketplace problems at scale, I'd love to chat.