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: • C ompetitive 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. About XPO 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. We are proud to be an Equal Opportunity employer. Qualified applicants will receive consideration for employment without regard to race, sex, disability, veteran or other protected status. All applicants who receive a conditional offer of employment may be required to take and pass a pre-employment drug test. The above statements are not an exhaustive list of all required responsibilities, duties and skills for this job classification. Review XPO's candidate privacy statement here .

Requirements

Must-haves

What you’ll need to succeed as a Machine Learning Engineer at XPO
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
3+ years of experience building ML infrastructure for training, evaluation, and deployment at scale
C ompetitive compensation package
Life and disability insurance
Earn up to 15 days of PTO over your first year
Education assistance
Opportunity to participate in a company incentive plan
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

Nice-to-haves

Master's degree in Computer Science or related field
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

Application prep

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Keywords to mirror

machine learningmlpythonsqlawsgcpci/cddockerkubernetesai

Platform: career-feeds
Effort: medium

Benefits

Benefits detected in the listing.

Health Insurance

401(K)

Pto