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Clera

Machine Learning Engineer

Clera San Francisco, California, United States

Technology, Information and Internet · 2-10 employees

8 h ago
machine-learning Mid (2-5 yrs) Full-time United States
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About the role

Design, build, and iterate on machine learning models for candidate-to-role matching and personalization. Develop and maintain data pipelines while monitoring model performance in production environments.

What they look for

Machine Learning PyTorch TensorFlow NLP Data Pipelines Model Training Model Deployment Recommendation Systems Statistics Computer Science Natural Language Understanding Model Monitoring Data Preparation

Requirements

Requires 3 to 7 years of hands-on experience in machine learning engineering with strong fundamentals in computer science or statistics. Proficiency in modern ML frameworks like PyTorch or TensorFlow and experience with NLP techniques are essential.

Full description

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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