As a Senior Machine Learning Engineer at Tebra, you will build, deploy, and optimize the machine learning services that power the Tebra platform. You will be the primary builder of robust ML subsystems, translating high-level requirements into production-ready code.
Requirements
- 5+ years of professional software development experience including system design, large-scale services, and production-grade infrastructure.
- 3+ years of hands-on experience in machine learning engineering or applied AI, with a strong record of deploying and maintaining models in production.
- Technical subject matter expertise in 3+ general areas of software development (e.g., server, database, security, etc) including machine learning infrastructure.
- Proficiency in Python, TensorFlow/PyTorch, and scikit-learn.
- Strong background in MLOps and data infrastructure (e.g., Airflow, Spark, feature stores, MLflow, data versioning).
- Familiarity with cloud ML environments (AWS, GCP, or Azure) and containerization (Kubernetes, Docker).
- Experience building or fine-tuning Large Language Models (LLMs) or generative models for structured business processes.
- Excellent technical communication and a product mindset—comfortable driving initiatives from concept to delivery.
Benefits
- Generous Paid Time Off
- 401k Matching
- Retirement Plan