Lead Machine Learning Engineer

$146,600 - $197,900/Yr

Total Wine - Bethesda, MD

Full-time - Mid Level

Bethesda, MD

Food and Beverage Retailers

About the position

Total Wine & More is seeking a Lead Machine Learning Engineer with expertise and a proven track record of deploying machine learning models into production, to join our Data Services team in Bethesda, MD. You will be responsible for enabling, automating, deploying, scaling and monitoring machine learning algorithms built by the data science team. You will work within current DevOps frameworks and make sure the data science teamwork is being deployed in an effective manner for production use. Working closely with software development and support teams, infrastructure, and security staff, you will enjoy learning and problem-solving in a fast-paced environment while being exposed to a diverse set of machine learning problems. As our team continues to grow, you will play an important part of our overall success and contribute to the value of the work produced by the data science team. You will report into the Director of Data Science and Analytics.

Responsibilities

• Manage and deploy machine learning models developed by Data Science team into production - integrated with the team through the development process.
• Support the retraining, monitoring, and measurement of deployed machine learning models - covering a wide spectrum of ML approaches.
• Create common frameworks for delivering modeling results to systems within TWM.
• Build out tools to support data scientists - lowering the level of effort to create and prototype machine learning models, such as building a feature data store.
• In collaboration with the Data Platform team, make sure ML results are published within TWM data warehouse and easily digestible by end users.
• In collaboration with Engineering and Architecture teams, build and maintain MLOps tools and frameworks - utilizing DevOps tools currently in place at Total Wine & More.
• In partnership with Data Science team members, maintain documentation and manage the transition of production processes to production support team, when applicable.

Requirements

• Bachelor's degree from four-year College or university in Computer Science, Mathematics, Statistics or related field. Master's or PhD preferred.
• 4-6+ years of experience in data science, computer science or related fields or 5+ years with Master's degree.
• 4-6+ years of experience in software engineering, data engineering, or related fields or 5+ years with Master's degree.
• Strong understanding of MLOps principles and practices with experience of supporting a data science team through the ML lifecycle to include deployment and monitoring.
• Experience with operationalizing, monitoring, and scaling machine learning models and pipelines in cloud ecosystems.
• Skills in handling and managing large datasets including, data cleaning, preprocessing, and storage. Deep understanding of batch and streaming pipelines as well as orchestrators like Argo and Airflow.
• Fundamental understanding of machine learning modeling techniques and algorithms. Experience using machine learning frameworks such as scikit-learn, pandas, numpy, xgboost, and pytorch.
• Solid programming skills in Python and the ability to write clean, efficient, and well-documented code.
• The ability to work effectively in a team and communicate complex ideas clearly with individuals from diverse technical and non-technical backgrounds.
• Familiarity with ML serving solutions like Ray, KubeFlow or W&B is a plus.
• The ability to present technical concepts and results in an audience-appropriate way
• Retail or similar experience a plus.
• Understanding of A/B testing

Nice-to-haves

• Familiarity with ML serving solutions like Ray, KubeFlow or W&B is a plus.
• Retail or similar experience a plus.

Benefits

• Paid Time Off (PTO)
• Generous store discounts
• Health care plans (medical, prescription, dental, vision)
• 401(k), HSA, FSA, Pre-tax commuter benefits
• Disability & life insurance coverage
• Paid parental leave
• Pet insurance
• Critical illness and accident insurance
• Discounted home and auto insurance
• College tuition assistance
• Career development & product training
• Consumer classes
• & More!