Clera
Machine Learning Engineer (Mid-Level)
About this role
Build and deploy machine learning systems that power core products in a fast-moving startup. You'll own the complete ML lifecycle from problem definition through production monitoring, collaborating with product and engineering teams to deliver models with measurable business impact.
What you'll do
- Design, train, and evaluate production ML models for real-world use cases
- Implement end-to-end ML pipelines including data preprocessing, model serving, and monitoring
- Translate business requirements into technical ML solutions with cross-functional teams
- Debug and optimize model performance in production based on feedback and metrics
- Write clean, maintainable code and contribute to ML infrastructure improvements
- Participate in code reviews and mentor teammates on ML best practices
What they're looking for
- Python for machine learning development
- ML frameworks (TensorFlow, PyTorch, or scikit-learn)
- Feature engineering and model evaluation
- MLOps tools and cloud ML platforms
- Docker and Kubernetes containerization
- Data pipeline design and maintenance
- A/B testing and experimentation frameworks
- Production ML systems deployment
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Clera
Clera builds an agentic operating system that automates complex workflows and processes through AI agents, with a platform designed to simplify distributed infrastructure management for developers. The company is hiring Founding Engineers, Customer Engineers, and Product Engineers to develop both backend systems and user-facing interfaces across their AI automation products.
View all jobs at CleraLikely interview questions
- Describe your experience taking a machine learning model from development to production—what were the biggest challenges?
- Walk us through how you've designed and optimized a data pipeline for a production ML system.