Machine Learning Engineer 1

About DAT

DAT is an award-winning employer of choice and a next-generation SaaS technology company that has been at the leading edge of innovation in transportation supply chain logistics for 45 years. We continue to transform the industry year over year, by deploying a suite of software solutions to millions of customers every day - customers who depend on DAT for the most relevant data and most accurate insights to help them make smarter business decisions and run their companies more profitably. We operate the largest marketplace of its kind in North America, with 400 million freights posted in 2022, and a database of $150 billion of annual global shipment market transaction data. Our headquarters are in Denver, CO, and Beaverton, OR, with additional offices in Seattle, WA; Springfield, MO; and Bangalore, India. For additional information, see www.DAT.com/company

 

Job Application Deadline: 06/30/2025

 

Candidate profile

As a Machine Learning Engineer I at DAT, you’ll join a cross-functional team focused on deploying, maintaining, and enhancing machine learning systems that power core parts of DAT’s product offerings. This entry-level role is ideal for those with foundational experience in ML engineering, who are eager to grow their skills in deploying ML solutions at scale and collaborating closely with researchers, engineers, and product stakeholders.

You will be instrumental in supporting the deployment of ML prototypes, maintaining production models, and ensuring they are well-integrated with the broader DAT platform.

What You’ll Do

• Help move prototype models from research to production environments
• Maintain and improve existing ML pipelines and services
• Refactor legacy codebases to align with current software best practices
• Monitor model health and performance, and contribute to model retraining efforts
• Build and support tools for training, deployment, rollback, and versioning of ML models
• Collaborate with researchers and engineers in code reviews, knowledge sharing, and cross-team initiatives

The Skills and Experience You’ll Bring

• Bachelor's or higher in Computer Science, Engineering, Statistics, Mathematics, or a related STEM field
• 1–2 years of experience in an ML engineer, data scientist, or software engineering role (or equivalent academic/project experience)
• Proficiency in Python and core libraries for data science (e.g., NumPy, pandas, scikit-learn)
• Familiarity with ML lifecycle concepts such as training, evaluation, deployment, and monitoring
• Basic understanding of SQL and version control (e.g., Git)

Bonus Skills 

Not required, but experience with the following will help you ramp up more quickly:

• Industry or academic experience in freight, logistics, or supply chain
• Familiarity with ML operations tools such as Airflow, MLflow, or SageMaker
• Working knowledge of CI/CD pipelines (GitHub Actions, Jenkins, etc.)
• Containerization using Docker or Kubernetes
• Snowflake or other cloud data warehouse experience
• Interest in infrastructure-as-code tools like Terraform

About the Team

• A collaborative and curious team with a culture of continuous learning
• Opportunities to work on impactful, real-world data science products
• Supportive mentorship from senior ML engineers and data scientists

 

Why DAT?
DAT is an award winning employer of choice.

For starters, we have a hybrid work environment, but we also know what makes a great workplace. We have a time-tested and resolute set of operating values predicated on integrity, mutual respect, open communication, and executing with excellence. These values inform our strategic vision as much as any one of our products does. We’ve been an employer of choice in the Portland metropolitan area for four decades, and within one year of opening our Denver office, DAT was #26 on Built In Colorado’s 100 Best Places to Work In Colorado.

• Medical, Dental, Vision, Life, and AD&D insurance
• Parental Leave
• Up to 20 days of paid time off starting in year one
• An additional 10 holi