Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent experience
1 year of software or machine learning engineering experience
Experience with data preparation and quality-checking for ML pipelines
Proficient in Python and SQL
Familiar with cloud data or ML platforms like AWS, GCP, or BigQuery
Strong collaboration skills with data science and engineering teams
Responsibilities
Build and maintain data preparation and validation tooling
Design and implement ML infrastructure for model training and deployment
Develop CI/CD pipelines for machine learning models
Implement model monitoring and drift detection
Partner with applied scientists to streamline model deployment
Collaborate with data engineering teams for data pipeline reliability
Contribute to MLOps tooling and best practices
Benefits
Full health insurance benefits available on day one
Life and disability insurance provided
Earn up to 15 days of PTO in the first year
9 paid company holidays
401(k) option with company match
Education assistance available
Opportunity to participate in a company incentive plan
Full Job Description
What you'll need to succeed as a Machine Learning Engineer at XPO
Minimum qualifications:
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
Preferred qualifications:
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
About the Machine Learning Engineer job
Pay, benefits and more:
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.
