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Clera

Machine Learning Engineer (Mid-Level)

Clera San Francisco, California, United States · $140K/yr

Technology, Information and Internet · 11-50 employees

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

Design, train, and deploy production machine learning models while building end-to-end ML pipelines. Collaborate with product and engineering teams to monitor, debug, and optimize model performance.

What they look for

Machine Learning Python TensorFlow PyTorch Scikit-learn MLOps AWS SageMaker GCP Vertex AI Kubernetes Docker Data Preprocessing Model Serving A/B Testing Feature Engineering Model Evaluation

Requirements

Requires at least 3 years of professional experience in machine learning or software engineering. Candidates must possess strong ML fundamentals and proficiency in Python along with experience in MLOps and cloud tools.

Full description

About the Role

As a Machine Learning Engineer, you'll build and deploy production machine learning systems for an AI-powered recruiting platform. You'll work across the ML lifecycle, partnering with product and engineering to turn business needs into reliable models and features.

What You'll Do

  • Design, train, and evaluate machine learning models for production use cases.
  • Build end-to-end ML pipelines, from data preprocessing through model serving and monitoring.
  • Collaborate with product and engineering teams to develop ML solutions for business needs.
  • Monitor, debug, and optimize production model performance using real-world feedback.
  • Write maintainable code and contribute to ML infrastructure and tooling.
  • Participate in code reviews and share knowledge with teammates.

What We're Looking For

  • At least 3 years of professional experience in machine learning or software engineering, including hands-on production ML work and employment after graduation.
  • A completed degree and experience in a substantive ML role at a product company or startup.
  • Strong ML fundamentals, including model selection, evaluation, feature engineering, and validation.
  • Proficiency in Python and practical experience with TensorFlow, PyTorch, or scikit-learn.
  • Experience building and maintaining production ML pipelines, including preprocessing, serving, and monitoring.
  • Familiarity with MLOps and cloud tools such as AWS SageMaker, GCP Vertex AI, Kubernetes, or Docker.
  • Experience with production A/B testing or experimentation, and comfort working in fast-moving environments.

Compensation & Benefits

Salary starts at $140,000 USD annually. Equity and visa sponsorship details were not provided.

Location

On-site in San Francisco, California, United States.

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