A Machine Learning Engineer responsible for developing, deploying, and maintaining predictive models to support Palmetto's clean energy initiatives, collaborating with data teams, and contributing to the company's MLOps platform.
Key Responsibilities
Design, train, and evaluate high-impact machine learning models across various business domains
Contribute to the creation and management of the core Machine Learning Platform and facilitate its adoption
Collaborate with Data Scientists and Data Engineers to develop, validate, and deploy feature pipelines for models
Implement practices for experimentation, validation, and performance analysis of models
Build tools for monitoring model drift, performance, and bias within the MLOps platform
Write clean, tested Python code for models and deployment logic
Requirements
Bachelor's degree in Computer Science, Engineering, or a related quantitative field or equivalent experience.
2-4 years of experience in machine learning or data science, focusing on building and deploying models.
Deep expertise in Python and proficiency in SQL.
Strong practice experience with statistical modeling toolkits such as PyTorch, XGBoost, Scikit-learn, TensorFlow, or VertexAI.
Familiarity with containerization and CI/CD concepts and comfort using MLOps platform.
Proven ability to understand business problems and think creatively about how machine learning might help solve them.
Employment is contingent upon the successful completion of a background check.
Benefits & Perks
unlimited PTO
medical coverage
dental coverage
vision coverage
paid parental leave
retirement plans
Ready to Apply?
Join Palmetto Clean Tech and make an impact in renewable energy