ML Infrastructure Engineer: Build & Deploy AI Pipelines

XPO Logistics, Inc.; Boston (MA); Hybrid; USD 100,000 - 120,000; Full time

Benefits offered by this job

Health insurance

PTO (up to 15 days in first year)

9 company holidays

401(k) with company match

Education assistance

Incentive plan participation

Job summary

XPO Logistics, Inc. is seeking a Machine Learning Engineer in Boston to design and build data preparation and validation tooling for ML inputs, and to implement ML infrastructure for end-to-end model development and deployment.

You will develop and maintain CI/CD pipelines for ML models, monitor drift, and collaborate with data science and data engineering teams to productionize experiments and ensure reliable data pipelines.

Qualifications

• Bachelor's degree or equivalent in CS/engineering or related field.
• 1 year of experience in software or ML engineering with data pipelines or ML infrastructure.
• Experience creating data prep/validation tooling for ML pipelines.
• Proficiency in Python and SQL.
• Experience with cloud data/ML platforms (AWS, GCP, BigQuery).
• Strong collaboration with data science and data engineering teams.

Responsibilities

• Build and maintain data preparation/validation tooling for ML inputs.
• Design and implement ML infrastructure for training, evaluation, deployment.
• Develop and maintain CI/CD pipelines for ML models with automated tests.
• Implement model monitoring, drift detection, and feedback loops in production.
• Collaborate with data scientists to productionize models and streamline deployment.

Skills

Python

SQL

Data pipelines

ML infrastructure

MLOps tooling

Collaboration

Education

Bachelor's degree in Computer Science/Engineering

Master's degree in Computer Science or related field

Tools

Docker

Kubernetes

CI/CD pipelines

Job description

XPO Logistics, Inc. is seeking a Machine Learning Engineer in Boston to design and build data preparation and validation tooling for ML inputs, and to implement ML infrastructure for end-to-end model development and deployment.

You will develop and maintain CI/CD pipelines for ML models, monitor drift, and collaborate with data science and data engineering teams to productionize experiments and ensure reliable data pipelines.