Senior AI & Data Science Tech Lead

XPO Enterprise Services, LLC; Boston (MA); Hybrid; USD 155,000 - 180,000; Full time

Benefits offered by this job

Health insurance

PTO 15 days first year

Company holidays

401(k) with company match

Education assistance

Incentive plan

Job summary

XPO is seeking a Technical Lead Manager for AI & Data Science to guide an interdisciplinary team of scientists and engineers in building production ML/AI systems, including multimodal GenAI and MLOps pipelines, across cloud environments.

The role emphasizes architecture reviews, code contributions, stakeholder updates, and driving measurable ROI from AI initiatives, with hybrid work in Boston and a competitive compensation package.

Qualifications

• Bachelor's degree or equivalent related work or military experience.
• 5 years of experience in Machine Learning Engineering, Applied AI, Data Science, or MLOps, including hands-on experience architecting and building production ML/AI systems.
• 2+ years of experience leading or acting as technical lead for a focused technical team.
• Experience reviewing model designs, code, and architecture tradeoffs; able to contribute code when needed.

Responsibilities

• Set the technical agenda for the team's AI/ML initiatives and allocate work.
• Architect end-to-end AI/ML systems and review model designs, code, and approaches.
• Contribute code directly on high-priority components when needed.
• Run daily standups and provide weekly status updates to management.
• Partner with software teams to integrate and deploy models into production.
• Mentor scientists and engineers on production-ready AI development.

Skills

ML Engineering

Applied AI

MLOps

Team Leadership

Production ML

Python

PyTorch

Data Platforms

AI Systems Design

Education

Bachelor's degree

Master's degree or PhD

Tools

Docker

Kubernetes

AWS

Azure

GCP

Vector Databases

Retrieval Systems

Job description

XPO is seeking a Technical Lead Manager for AI & Data Science to guide an interdisciplinary team of scientists and engineers in building production ML/AI systems, including multimodal GenAI and MLOps pipelines, across cloud environments.

The role emphasizes architecture reviews, code contributions, stakeholder updates, and driving measurable ROI from AI initiatives, with hybrid work in Boston and a competitive compensation package.