Machine Learning Engineer

About Shipwell

At Shipwell, we empower supply chain efficiency and service effectiveness at scale. The 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 FreightWaves’ FreightTech 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 DevOps 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 (GitHub, GitLab) and Agile methodologies
• Experience with agentic tooling and pipelines including LangChain, LangGraph, and LangSmith
• Bachelor's Degree in a quantitative field such as Physics, Engineering, Computer Science, or demonstrated equivalent quantitative experience