Machine Learning Engineer (Mid-Level)

About the role

ABOUT THE ROLE

Build and deploy production machine learning systems in a fast-moving product environment. You will own work across the ML lifecycle, partnering with product, engineering, and domain experts to deliver models that address real business needs.

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.

- Work with product and engineering partners to turn business requirements into ML solutions.

- Debug and improve production model performance using monitoring data and real-world feedback.

- Write maintainable code and contribute to ML infrastructure and tooling.

- Participate in code reviews and share technical knowledge with teammates.

WHAT WE'RE LOOKING FOR

- At least 3 years of professional machine learning or software engineering experience, including hands-on ownership of production ML systems in a startup or fast-moving product environment.

- 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 production ML pipelines that cover data preprocessing, model serving, and monitoring.

- Experience deploying and maintaining ML systems at scale with tools or platforms such as AWS SageMaker, GCP Vertex AI, Kubernetes, or Docker.

- Experience with production A/B testing or experimentation frameworks, and optimizing models based on results.

- A completed university degree and professional employment experience after graduation.

- Ability to work through ambiguity and prioritize practical impact in a dynamic environment.

LOCATION

On-site in San Francisco, California.

See the posting on Clera's site