ML Engineer

Job Description

With an enterprise-wide view of data and machine learning initiatives, design scalable and repeatable solutions to machine learning and AI projects that impact and influence the company s analytics strategy, including designing platforms and APIs for models Design and steer the policies and patterns for how other teams interface with machine learning models. Strategically understand and devise solutions for how to incorporate new machine learning + AI solutions into our tech stack across a wide variety of use cases Establish best practices across machine learning engineering team to enable and accelerate multiple critical support use cases Lead a team of experts to continuously monitor deployed models, build scalable solutions to identify data issues such as detecting data drift and model drift of new and existing machine learning processes Keep up with ML Ops technology trends and vendors to understand new capabilities and continuously innovate Subject matter expert for building processes that ensure reproducibility of models by supporting versioning of data and code, CI/CD, containerization (Kubernetes) Education/Work Experience: Masters degree in Computer Science, Information Systems, Machine Learning, Data Science, or a related field. Proficiency in programming languages such as Python, and experience with machine learning libraries (e.g., TensorFlow, PyTorch, scikit-learn). 12 - 15 years relevant experience working with production machine learning pipelines. PREFERRED: Master s degree in a STEM field with 5+ years of relevant work experience Skill Requirements: Must demonstrate the ability to manage stakeholders, the capacity to think strategically, and the aptitude to coach, mentor, and manage highly technical FTEs.