Mid-Level Machine Learning Engineer

Clera; San Francisco (CA); On-site; USD 140,000 - 180,000; Full time

Job summary

Clera Labs, Inc. in San Francisco is seeking an ML Engineer to own the full ML lifecycle, from problem framing to production monitoring. You will partner with product, engineering, and domain experts to deliver impactful ML outcomes.

Responsibilities include designing and deploying models, building end-to-end pipelines, and improving production performance with real-world feedback. Strong Python and ML framework experience required.

Qualifications

• Completed university degree in a relevant field.
• 3+ years of professional experience in ML or software engineering.
• Hands-on experience building production ML systems in a startup/rapid team.
• Strong understanding of model selection, evaluation, and feature engineering.

Responsibilities

• Design, train, and evaluate machine learning models for production use cases.
• Build end-to-end ML pipelines including data preprocessing, serving, and monitoring.
• Collaborate with product and engineering to translate business needs into ML solutions.
• Debug and improve production model performance using monitoring data.
• Write maintainable code and contribute to ML infrastructure and tooling.
• Participate in code reviews and share knowledge with teammates.

Skills

Python

ML engineering

Production ML

A/B testing

Ambiguity tolerance

Education

Bachelor's degree in CS/Math/Related

Tools

TensorFlow

PyTorch

scikit-learn

AWS SageMaker

Docker

Kubernetes

Job description

About the Role

Build and deploy machine learning systems for a fast-moving technology product team. You will own work across the ML lifecycle, from defining problems to monitoring models in production, partnering with product, engineering, and domain experts to deliver useful outcomes.

What You'll Do

• Design, train, and evaluate machine learning models for production use cases.

• Build end-to-end ML pipelines spanning data preprocessing, model serving, and monitoring.

• Work with product and engineering partners to turn business needs 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 knowledge with teammates.

What We're Looking For

• A completed university degree and at least 3 years of professional experience in machine learning or software engineering, including post-graduation employment.

• Hands-on experience building and deploying production ML systems in an ML engineering role at a startup or fast-moving product company.

• Strong understanding of model selection, evaluation metrics, feature engineering, and validation techniques.

• Proficiency in Python and hands-on experience with TensorFlow, PyTorch, or scikit-learn.

• Experience implementing and maintaining production ML pipelines, including preprocessing, model serving, and monitoring at scale.

• Experience with MLOps tools or cloud platforms such as AWS SageMaker, GCP Vertex AI, Kubernetes, or Docker.

• Experience with production A/B testing or experimentation, and optimizing models based on observed performance.

• Comfort working through ambiguity and iterating quickly in a product environment.

Location

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