Machine Learning Engineer (Mid-Level)

About the Role

As a Machine Learning Engineer at Clera, you'll build and deploy ML systems that power our core product in a fast-moving startup environment. You'll work across the full ML lifecycle—from problem definition through production monitoring—collaborating 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 applied ML work in production systems.
• Experience working in startup or fast-moving product environments with rapid iteration cycles.
• Strong fundamentals in machine learning (model selection, evaluation, feature engineering, and validation).
• Proficiency in Python or similar languages used for ML development, and common ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
• Experience building, deploying, and maintaining ML systems at scale, including aspects like A/B testing, monitoring, data pipelines, and MLOps tools (e.g., AWS SageMaker, GCP Vertex AI, Kubernetes, Docker).
• Comfort with ambiguity and ability to prioritize impact in a dynamic setting.