Machine Learning Engineer (Mid-Level)

Clera; San Francisco (CA); On-site; USD 120,000 - 150,000; Full time

Job summary

Clera is seeking a skilled ML Engineer to join our San Francisco headquarters to build and deploy ML systems powering a fast moving product. You will design, train, and deploy models, implement end-to-end pipelines, and collaborate with product and engineering teams to ship impactful ML solutions in production.

Strong Python and ML framework experience required. Join a fast-paced startup environment and contribute to ML infrastructure, monitoring, and data pipelines while delivering real world

Qualifications

• 3+ years of professional experience in machine learning or software engineering with hands on applied ML in production systems.
• Experience in startup or fast moving product environments with rapid iteration cycles.
• Strong fundamentals in model selection, evaluation, feature engineering and validation.
• Proficiency in Python or similar languages and ML frameworks such as TensorFlow, PyTorch or scikit learn.
• Experience building, deploying and maintaining ML systems at scale including A/B testing, monitoring, data pipelines and MLOps tools such as cloud ML platforms and container technologies.
• Comfort with ambiguity and ability to prioritize impact in a dynamic setting.

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 and iterate 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

Python proficiency

MLOps familiarity

Production ML experience

Tools

TensorFlow

PyTorch

Scikit-learn

Docker

Job description

About the Role

Work on building and deploying ML systems that power a fast moving product. You will contribute across the full ML lifecycle and collaborate with product and engineering teams to ship models that make a real 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 and iterate 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 applied ML in production systems.

• Experience in startup or fast moving product environments with rapid iteration cycles.

• Strong fundamentals in model selection, evaluation, feature engineering and validation.

• Proficiency in Python or similar languages and ML frameworks such as TensorFlow, PyTorch or scikit learn.

• Experience building, deploying and maintaining ML systems at scale including A/B testing, monitoring, data pipelines and MLOps tools such as cloud ML platforms and container technologies.

• Comfort with ambiguity and ability to prioritize impact in a dynamic setting.

Location

On site at our San Francisco, CA headquarters. Primary location: San Francisco, California, United States.