Machine Learning Engineer - Hybrid

• Bachelor’s degree in Computer Science, Engineering, or related field, or equivalent related work or military experience
• 1 year of experience in software or machine learning engineering, including hands-on experience building data pipelines, ML infrastructure, or MLOps tooling
• Experience developing data preparation, validation, or quality-checking tooling for machine learning pipelines
• Proficiency in Python and SQL
• Experience with cloud data or ML platforms (e.g., AWS, GCP, BigQuery)
• Strong collaboration skills, with experience partnering with data science/applied science teams and data engineering teams, * Master’s degree in Computer Science or related field
• 3+ years of experience building ML infrastructure for training, evaluation, and deployment at scale
• Experience building and maintaining CI/CD pipelines for machine learning models
• Experience with model serving and inference infrastructure (batch and real-time)
• Experience implementing model monitoring, drift detection, and feedback-loop tooling
• Experience with containerization and orchestration (Docker, Kubernetes)
• Experience partnering with data engineering teams on data pipeline reliability and access

• Competitive compensation package
• Full health insurance benefits available on day one
• Life and disability insurance
• Earn up to 15 days of PTO over your first year
• 9 paid company holidays
• 401(k) option with company match
• Education assistance
• Opportunity to participate in a company incentive plan

What you’ll do on a typical day:

• Build and maintain data preparation and validation tooling to ensure high-quality inputs for ML and optimization models
• Design and implement ML infrastructure for model training, evaluation, and deployment
• Build and maintain CI/CD pipelines for machine learning models, including automated testing and validation
• Implement model monitoring, drift detection, and feedback loops to track model performance in production
• Partner with applied and data scientists to productionize models and streamline the path from experimentation to deployment
• Collaborate with data engineering teams to ensure reliable, accessible data pipelines
• Contribute to shared MLOps tooling and best practices across the AI/ML organization

Annual Salary Range: $100,000 to $120,000 Actual compensation may vary due to factors such as experience and skill set. This is an incentive-based position, which may include bonuses, incentive or commission plans.

XPO is a top ten global provider of transportation services, with a highly integrated network of people, technology and physical assets. At XPO, we look for employees who like a challenge and can communicate effectively in all situations. We want to leverage your skills and years of experience to drive positive results while ensuring a bright future for yourself and XPO. If you’re looking for a growth opportunity, join us at XPO.