Machine Learning Engineer (Mid-Level)

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.