Machine Learning Engineer Job Washington area,District of Columbia USA,IT/Tech

About Shipwell

At Shipwell, we empower supply chain efficiency and service effectiveness Shipwell platform includes capabilities previously out of most shippers' technical reach and affordability today. Our solution combines everything shippers need, from transportation management and visibility to procurement, in a comprehensive, easy-to-use platform. It will adapt and scale as market and business demand change, allowing shippers to operate, manage, and optimize the shipping process seamlessly.

Industry experts have recognized Shipwell's traction in the market and have differentiated Shipwell as a leader in the logistics industry. Awards include Gartner Magic Quadrant for TMS 2025, 2024, 2023, 2022, 2021, Food Logistics’ 2024 Top Software & Technology Providers, and Freight Waves’ Freight Tech 2022 and 2021 Awards for Innovation and Disruption in Freight Industry. Shipwell was also named the fourth fastest-growing company in North America on the 2021, 2022, and 2023 Deloitte Technology Fast 500 and Forbes 2020 Next Billion-Dollar Startup.

Our Culture

Shipwell is a fast-paced, high-energy start-up that strives to build the future of shipping every day. Diversity of thought and cross-department collaboration is very important to us. We deliver open, honest, careful communication and work as hard as we play. We create & deliver solutions that are revolutionizing the industry, which brings excitement and purpose to our work. If you are looking for a place that will help you tap into your best work-self and give you hands-on experience building something big, then we invite you to come and build the future of shipping with us!

About the Role

As a Machine Learning Engineer at Shipwell, you'll play a pivotal role in building and scaling our AI-powered logistics solutions. You'll design, develop, and maintain the data pipelines and ML infrastructure that power our autonomous digital workers and drive data-driven decision-making across the organization.

Your work will span the full machine learning lifecycle—from extracting and transforming data from diverse sources to implementing production-grade ML models in our cloud environment. You'll optimize our AWS infrastructure, establish data integrity standards, and create scalable architectures that enable research teams to access the data they need. Working closely with engineering, analytics, data science, and product teams, you'll take our machine learning capabilities to the next level.

This is a dynamic opportunity to become the expert on Shipwell's ML and data infrastructure, make critical technical decisions, and contribute to projects at the forefront of GenAI and machine learning in the logistics industry. You'll own the processes you create and have the opportunity to grow your skills while revolutionizing how the supply chain operates.

What we’re looking for:

Experience designing and implementing ML models and maintaining relevant data in AWS
Experience working with Dev Ops to enable your team access to the tools they need
Contributing to every part of the machine learning product lifecycle
Proven track record of implementing data engineering best practices in all aspects of the data pipeline, i.e. ETL, data integrity, and monitoring
Demonstrable proficiency with Python, dbt, SQL, and modern ML tooling
Experience working with large-scale data model refactoring for better performance, interpretability, and maintainability
Experience with version control tools (Git Hub, Git Lab) and Agile methodologies.
Experience with agentic tooling and pipelines including Lang Chain, Lang Graph, and Lang Smith
Bachelor's Degree in a quantitative field such as Physics, Engineering, Computer Science, or demonstrated equivalent quantitative experience.
Excellent communication skills to effectively collaborate with different teams within the engineering org

What you’ll do when you get here:

Collaborate closely with our engineering, analytics, data science, and product teams as we take our machine learning projects and infrastructure to the next level
Right at the start you will be contributing to existing ML projects, creating and maintaining the data pipelines they need, and…