MLOps Engineer

Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, or related quantitative field. 3+ years of experience in data engineering or machine learning with MLOps success. Proven expertise in designing and implementing ML testing strategies. Expertise in deploying ML models at scale on AWS, using MLFlow or similar. Strong Python programming skills and adherence to software engineering best practices. Expert-level SQL skills and experience with large datasets. Strong problem-solving skills. Excellent communication and collaboration skills.

Develop and implement end-to-end machine learning features for revenue optimization. Establish and maintain robust MLOps practices including CI/CD for model training, testing, deployment, and monitoring. Design, build, and maintain highly reliable data and ML pipelines. Utilize Apache Airflow for managing complex data and ML workflows. Implement comprehensive software quality and testing processes for ML systems. Design, train, and test machine learning models for pricing optimization. Implement model performance monitoring. Collaborate cross-functionally to define SLIs/SLOs and improve system performance. Conduct A/B testing and experimentation to validate model effectiveness.