Machine Learning Engineer

RADAR is seeking a Machine Learning Engineer to enhance and develop its machine learning capabilities. This role involves close collaboration with various teams, including product, customer success, engineering, data science, and research, to drive the company's mission of transforming physical retail through cutting-edge technology.

The Machine Learning Engineer will be responsible for designing and maintaining scalable, reliable, and efficient production pipelines for feature engineering, training, prediction, and model serving. Key tasks include training, validating, and deploying high-quality machine learning models, optimizing feature engineering pipelines, implementing comprehensive model monitoring, and applying CI/CD principles to ensure model health and performance.

Candidates should have over five years of experience building production machine learning systems at scale, with strong proficiency in Python and machine learning frameworks such as scikit-learn, PyTorch, and XGBoost. Hands-on experience with cloud machine learning platforms like AWS SageMaker, Vertex AI, or Azure ML is essential. Expertise in big data processing, including SQL optimization and distributed computing with Spark or Dask, as well as experience with workflow orchestration tools like Airflow, Dagster, or Prefect, is required. Proficiency with version control systems (Git) and CI/CD practices is also necessary.

The expected base salary range for this position is $160,000 to $200,000 annually. Additional benefits include equity, comprehensive medical and dental coverage, life and disability benefits, a 401(k) plan, flexible time off, and paid parental leave.

RADAR fosters a mission-driven and collaborative environment where bold ideas and impactful contributions are valued. The company emphasizes clear communication, balanced work-life integration, diverse perspectives, and empathy-driven design, making it an ideal workplace for those passionate about transforming retail with innovative technology.