Machine Learning Engineer
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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 they'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.
- A bias toward action, strong ownership mentality, and comfort with ambiguity in a small team setting.
Nice to have
- Experience at a high-performing technology company or consulting environment is a plus.
Summarised by NextRaise from the employer’s description, which follows in full below.
Full description from employer
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.
Company
Company facts come from this company's own listings. We only show what the postings themselves carry.