Technical Lead Manager, Machine Learning

🔥 11 minutes ago

🏄 California – Remote

🏄 California – Remote

💵 $210k - $240k / year

⏰ Full Time

🟠 Senior

🤖 Machine Learning Engineer

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Veho

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 2016

📦 Logistics

🛍️ eCommerce

🤝 B2B

💰 $170M Series B - Veho on 2022-02

Logistics • eCommerce • B2B

Veho is a tech-enabled last-mile delivery and logistics company that provides e-commerce-focused delivery and fulfillment services to retailers and marketplaces. It operates a network of drivers, routes, and local hubs to offer fast, reliable parcel delivery and improve customer experience, positioning itself as a B2B partner for online merchants seeking optimized shipping and delivery operations.

📋 Description

• Lead and grow a team of six data scientists / applied ML engineers building production models across route success, last mile route building, and forecasting • Deeply understand the highest-leverage problems, partner with your team to choose the ML / OR methodologies, and drive models from the first prototype through deployment, monitoring, and iteration • Ship and maintain production systems. You'll personally build, deploy, and maintain models in production. You stay in the codebase, review your team's PRs, and debug a failing model or a broken pipeline yourself when needed • Partner closely with the ML Platform / ML Operations team so models deploy on stable infrastructure, and push modeling requirements back into the platform so the next project is faster • Drive AI usage across the modeling workflow. Set standards, introduce patterns, and drive adoption of how to leverage AI in data science work (EDA, feature and model iteration, ML methodologies) • Be part of the on-call rotation for our data science production systems

🎯 Requirements

• Bachelor's Degree plus at least 6 years of experience in Machine Learning Engineering or Data Science, or Master's Degree plus at least 4 years • hands-on experience building, deploying, and owning ML models in production end to end, not handed off to a separate engineering team • depth in relevant modeling domains: time-series forecasting, causal inference, telemetry analysis • experience managing impactful, high-velocity applied ML / data science teams in smaller-scale companies • experience leveraging AI to accelerate development and analysis • Strong knowledge of Cloud-based data science tooling (AWS preferred) and Data Warehouses (Redshift, Databricks, Snowflake) • Strong knowledge of production ML practices: experimentation, model monitoring, retraining, and working alongside an ML platform / MLOps team • Strong proficiency in Python • Knowledge of building systems in a Supply Chain setting, enabling a physical supply chain to run like clockwork

🏖️ Benefits

• comprehensive medical, dental, and vision coverage • 401k • generous PTO