Machine Learning Engineer; Mid-Level

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.

• 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.

• 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 Tensor Flow, 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 Sage Maker, 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.