Machine Learning Engineer

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Machine Learning Engineer in USA new

Clera
Full time
Email

USA
09/21/2026
Report

San Francisco, CA

Responsibilities

Design, train, and evaluate machine learning models for production use cases.
Build end-to-end ML pipelines for data preprocessing, model serving, and monitoring.
Translate business requirements into machine learning solutions with product and engineering teams.
Debug and optimize model performance in production using real-world feedback.
Write maintainable code and contribute to ML infrastructure and tooling.
Participate in code reviews and share knowledge across the team.

Requirements

3–7 years of professional experience in machine learning or software engineering with hands-on applied ML work in production systems.
Experience working in a startup or similarly fast-paced, resource-constrained environment.
Strong fundamentals in model selection, evaluation, feature engineering, and validation.
Proficiency in Python and common ML frameworks such as TensorFlow, PyTorch, or scikit-learn.
Experience building, deploying, and maintaining ML systems at scale rather than only academic or prototype systems.
Experience with data pipelines, feature engineering, or model evaluation in production contexts.
Familiarity with cloud ML platforms or MLOps tooling such as AWS SageMaker, GCP Vertex AI, Kubernetes, or Docker is preferred.
Experience with A/B testing, experimentation frameworks, or production model monitoring is preferred.
Ability to prioritize impact and work comfortably with ambiguity in a dynamic environment.

Benefits

Based in San Francisco, California; specific work arrangement should be confirmed directly with the team.

Clera

Clera harnesses the power of artificial intelligence to match high-growth startups with exceptional talent, streamlining the entire headhunting process. This innovative approach simplifies the job search for candidates while providing startups with access to a curated pool of skilled professional...

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