Technical Lead Manager, Machine Learning

This is a fully remote position, open to applicants in California.

📋 Description

• Lead and expand a team of six data scientists and applied ML engineers developing production models focused on route success, last mile route optimization, and forecasting.

• Gain a comprehensive understanding of the most impactful challenges, collaborate with your team to select the appropriate ML/OR methodologies, and guide models from initial prototyping to deployment, monitoring, and refinement.

• Deliver and support production systems. You will personally construct, deploy, and maintain models in a production environment, actively engage with the codebase, review your team's pull requests, and troubleshoot any failing models or broken pipelines as necessary.

• Collaborate closely with the ML Platform/ML Operations team to ensure models are deployed on reliable infrastructure, while also influencing modeling requirements to streamline future projects.

• Promote the utilization of AI throughout the modeling workflow. Establish standards, introduce methodologies, and encourage the adoption of AI in data science tasks (such as exploratory data analysis, feature and model iteration, and ML methodologies).

• Participate in the on-call rotation for our data science production systems.

⛳️ Requirements

• Bachelor’s Degree with a minimum of 6 years of experience in Machine Learning Engineering or Data Science, or a Master’s Degree with at least 4 years of experience.

• Practical experience in building, deploying, and managing ML models in production from start to finish, rather than passing off to a separate engineering team.

• Extensive knowledge in relevant modeling domains, including time-series forecasting, causal inference, and telemetry analysis.

• Experience leading effective, high-velocity applied ML/data science teams within smaller-scale organizations.

• Proficiency in utilizing AI to enhance development and analytical processes.

• Strong familiarity with cloud-based data science tools (AWS preferred) and data warehouses (such as Redshift, Databricks, Snowflake).

• In-depth knowledge of production ML practices including experimentation, model monitoring, retraining, and collaboration with an ML platform/MLOps team.

• High proficiency in Python.

• Understanding of system development in a Supply Chain environment, ensuring operational efficiency.

🏝️ Benefits

• Comprehensive medical, dental, and vision coverage.

• 401k plan.

• Generous paid time off (PTO).