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 lifecyclerom 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 were 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.
- Excellent communication skills to effectively collaborate with different teams within the engineering org
What Youll 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 communicate the results to the organization
- You will own all of the data and ML processes you create
- You will become the expert on our machine learning and data infrastructure and make critical decisions in our path forward
- You will have the opportunity to grow your skill set and take part in projects at the forefront of GenAI, ML, and data science in the logistics industry
