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Salary
$181k – $347k per year (Estimated)
Location
Remote/Hybrid (San Francisco, United States)
Seniority
Middle · 3+ years exp
Employment
Full-Time
Overview
Company
Impact
Profile match
Clera is a San Francisco company that runs an AI recruiting platform positioned as a talent agent rather than a job board, matching engineers and other technical candidates to roles at venture-backed startups. Its system reads a candidate's background and preferences, then represents them to hiring teams at companies funded by firms such as Andreessen Horowitz, Y Combinator, Index Ventures and General Catalyst, compressing the introduction step that traditional headhunting handles manually. The model is aimed at the segment where recruiter fees are highest and candidate supply is thinnest, and the platform handles screening, scheduling and pipeline tracking for both sides of the match.

About the Role

We are a small, fast-moving AI-powered recruitment tech startup, and we are looking for a mid-level Machine Learning Engineer to help build and improve the core matching and recommendation systems that connect candidates with the right opportunities. This is a high-impact role at a company where your work will directly shape the product and the experience of thousands of job seekers and hiring teams.

What You'll Do

  • Design, build, and iterate on machine learning models that power candidate-to-role matching and personalization.

  • Work closely with the founding team to translate product goals into scalable ML solutions.

  • Develop and maintain data pipelines to support model training, evaluation, and deployment.

  • Monitor model performance in production and drive continuous improvements.

  • Contribute to research and experimentation on new AI techniques relevant to talent matching and natural language understanding.

What We're Looking For

  • 3 to 7 years of hands-on experience in machine learning engineering or a closely related role.

  • Strong fundamentals in computer science, statistics, or a related quantitative field.

  • Proven experience building and deploying ML models in production environments.

  • Proficiency with modern ML frameworks such as PyTorch or TensorFlow, and familiarity with NLP techniques.

  • Comfort working across the full ML lifecycle, from data preparation through to model monitoring.

  • Experience at a high-performing technology company or consulting environment is a plus.

  • A bias toward action, strong ownership mentality, and comfort with ambiguity in a small team setting.

Location

Based in San Francisco, California. This is an on-site or hybrid role at our San Francisco office.

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