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Clera

Mid-Level Machine Learning Engineer

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

Technology, Information and Internet · 11-50 employees

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

You will design, train, and deploy production machine learning models while building end-to-end pipelines. Additionally, you will collaborate with product and engineering teams to optimize model performance and maintain infrastructure.

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 Model Monitoring Feature Engineering Software Engineering

Requirements

Candidates must have at least 3 years of professional experience in machine learning or software engineering with strong fundamentals in model development. Proficiency in Python and experience with MLOps tools and cloud platforms are required.

Full description

About the Role

Build and operate production machine learning systems at an early-stage AI recruiting and talent technology company. You will own work across the ML lifecycle, partnering with product, engineering, and domain experts to deliver models that support the core product.

What You'll Do

  • Design, train, and evaluate machine learning models for production use cases.
  • Build end-to-end ML pipelines, including data preprocessing, model serving, and monitoring.
  • Partner with product and engineering teams to turn business needs into ML solutions.
  • Debug and improve production model performance using monitoring and 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 machine learning or software engineering experience, including building and deploying production ML systems.
  • Strong ML fundamentals, including model selection, evaluation, feature engineering, and validation.
  • Proficiency in Python and hands-on experience with TensorFlow, PyTorch, or scikit-learn.
  • Experience implementing end-to-end ML pipelines and maintaining deployed systems at scale.
  • Familiarity with MLOps and cloud platforms or tools such as AWS SageMaker, GCP Vertex AI, Kubernetes, or Docker.
  • Experience with production A/B testing or experimentation, and debugging models based on operational feedback.
  • Background in a startup or fast-moving, product-focused environment, plus completed university studies and professional employment after graduation.

Compensation & Benefits

Base salary starts at $140,000 USD annually. The upper end of the range was not provided. Visa sponsorship policy was not provided.

Location

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

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