Machine Learning Engineer (Mid-Level)

Clera Labs, Inc.; San Francisco (CA); Hybrid; USD 150,000 - 210,000; Full time

Job summary

Clera Labs, Inc. is seeking a Machine Learning Engineer to design, build, and deploy ML systems powering our core product in a fast-moving startup environment.

You will own the full ML lifecycle—from problem definition through production monitoring—working closely with product, engineering, and domain experts to ship models that drive real business impact. You will design, train, and evaluate production-ready models, implement end-to-end ML pipelines, and collaborate across teams to translate

Qualifications

• 3+ years of professional experience in machine learning or software engineering.
• Strong fundamentals in machine learning, including model selection, evaluation, feature engineering, and validation.
• Experience with end-to-end ML pipelines, including data preprocessing, model serving, and monitoring.

Responsibilities

• Design, train, and evaluate machine learning models for production use cases.
• Implement end-to-end ML pipelines from data preprocessing to model serving and monitoring.
• Collaborate with product and engineering teams to translate business requirements into ML solutions.
• Debug and optimize model performance in production, iterating based on real-world feedback.
• Write clean, maintainable code and contribute to ML infrastructure and tooling.
• Participate in code reviews and share knowledge with the broader team.

Skills

ML fundamentals

Model evaluation

Ambiguity tolerance

Tools

Python

TensorFlow

PyTorch

scikit-learn

AWS SageMaker

GCP Vertex AI

Kubernetes

Docker

Job description

About the Role

As a Machine Learning Engineer at Clera, you'll design, build, and deploy ML systems that power our core product in a fast-moving startup environment. You'll own the full ML lifecycle—from problem definition through production monitoring—working closely with product, engineering, and domain experts to ship models that drive real business impact.

What You'll Do

• Design, train, and evaluate machine learning models for production use cases.
• Implement end-to-end ML pipelines, from data preprocessing to model serving and monitoring.
• Collaborate with product and engineering teams to translate business requirements into ML solutions.
• Debug and optimize model performance in production, iterating based on real-world feedback.
• Write clean, maintainable code and contribute to ML infrastructure and tooling.
• Participate in code reviews and share knowledge with the broader team.

What We're Looking For

• 3+ years of professional experience in machine learning or software engineering, with hands-on work building and deploying production ML systems.
• Strong fundamentals in machine learning, including model selection, evaluation, feature engineering, and validation.
• Proficiency in Python and experience with common ML frameworks such as TensorFlow, PyTorch, or scikit-learn.
• Experience implementing end-to-end ML pipelines, including data preprocessing, model serving, and monitoring at scale.
• Familiarity with MLOps tools and cloud ML platforms such as AWS SageMaker, GCP Vertex AI, Kubernetes, or Docker.
• Experience with A/B testing and experimentation frameworks in production environments.
• Background working in startup or fast-moving product environments with rapid iteration cycles.
• Comfort with ambiguity and ability to prioritize impact in a dynamic setting.