Build, deploy, and optimize the machine learning services that power the Tebra platform
Write high-quality, production-grade software for data ingestion, feature extraction, and model inference
Implement robust CI/CD pipelines, automated testing, and comprehensive logging for deployed models
Construct and maintain specific data pipelines for training and inference
Develop reusable software modules and utilities to streamline the development process
Translate business requirements into technical specifications
Monitor the daily performance of production models and debug incidents

Requirements

5+ years of professional software development experience
3+ years of hands-on experience in machine learning engineering or applied AI
Technical subject matter expertise in 3+ general areas of software development
Demonstrated ability to deliver significant, measurable real-world impact through applied ML
Proven ability to design and write modular, performant, and easy to read software
Proficiency in Python, TensorFlow/PyTorch, and scikit-learn
Strong background in MLOps and data infrastructure (e.g., Airflow, Spark)
Proven ability to deploy and maintain ML models in production
Familiarity with cloud ML environments (AWS, GCP, or Azure)
Experience building or fine-tuning Large Language Models (LLMs)
Experience with retrieval-augmented pipelines or feedback-driven model retraining
Excellent technical communication and a product mindset

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

machine learningdata ingestionfeature extractionmodel inferenceCI/CD pipelinesautomated testingdata pipelinesPythonTensorFlowPyTorch

Soft Skills

technical communicationproduct mindset