Participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms
Focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of machine learning applications
Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications
Inform ML infrastructure decisions using understanding of ML modeling techniques and issues
Design, build, and deliver ML models and components that solve real-world business problems
Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment
Retrain, maintain, and monitor models in production
Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale
Construct optimized data pipelines to feed ML models
Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and ML follows best practices in Responsible and Explainable AI

Bachelor’s Degree
At least 6 years of experience designing and building data-intensive solutions using distributed computing
At least 4 years of experience programming with Python, Scala, or Java
At least 2 years of experience building, scaling, and optimizing ML systems
Master's or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field (preferred)
3+ years of experience building production-ready data pipelines that feed ML models (preferred)
3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow (preferred)
2+ years of experience developing performant, resilient, and maintainable code (preferred)
2+ years of experience with data gathering and preparation for ML models (preferred)
2+ years of people leader experience (preferred)
1+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation (preferred)
Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform (preferred)
Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance (preferred)

Performance based incentive compensation
Cash bonus(es)
Long term incentives (LTI)
Comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being

Lead Machine Learning Engineer

Key skills