About the Team
The Uber Freight team is building a better future for shipping. We believe that when shippers and carriers have the freedom to move together, the entire industry moves ahead. Our teams design and build innovative applications, infrastructure, and models to power Uber Freight. Utilizing Uber's foundational elements, these include the mobile app for Carriers, the portals and integrations that give Shipper’s access to the platform, tools for our Operations teams, and all the underlying pricing, matching, and forecasting algorithms that evolve the freight industry forward.
What the candidate will do
As a Senior Engineer you will drive the development of high-impact solutions for Uber Freight’s marketplace and operations by leveraging a deep foundation in traditional machine learning alongside emerging Generative AI applications. You will spearhead the end-to-end lifecycle of predictive models—from identifying step-change opportunities and researching advanced techniques to overseeing rapid prototyping and robust production monitoring at scale. While your primary focus will be on optimizing logistics operations and network effects through core ML, you will also guide the team in integrating GenAI and Agentic systems where they drive the most business value, collaborating with cross-functional stakeholders to deliver scalable, production-ready models that redefine efficiency.
Basic Qualifications
- Bachelor’s degree in Computer Science, Computer Engineering, or related fields
- At least 5+ years of Software Engineering or ML Engineering experience
- Experience in one or more programming languages including Python, Go or Java
- Proven experience with designing and implementing machine learning models in production environments with large data sets
- Experience in communicating algorithm choices, ML system design & concepts to leadership, technical peers & industry experts
- Strong adherence to metrics driven development, with a disciplined and analytical approach to product development
Preferred Qualifications
- MS or PhD degree in Computer science, Data Science, ML or equivalent practical experience
- Deep understanding of ML theory and a broad toolkit of algorithms, including deep learning, instance-based learning, and traditional statistical models
- Experience with designing and implementing machine learning models in production environments applied to generative AI, applications of large language models
- Experience in stream processing--Storm, Spark, Flink etc.-- and graph processing technologies.
Benefits & Compensation for U.S. Employees
Employees working more than 30 hours in the US at Uber Freight are eligible for benefits like a company sponsored health plan, dental and vision benefits, 401k match, financial and mental wellness benefits, parental leave, short- and long-term disability coverage, life insurance and more. US based employees may also be eligible for a performance or sales incentive bonus program, participation in Uber Freight equity awards, and other types of compensation depending upon the role.
About Uber Freight
Uber Freight helps companies move goods more reliably and efficiently. We bring together the technology, people, and transportation capacity they need, using real‑time data from millions of shipments to guide smarter decisions. That helps customers spot issues early, avoid costly surprises, and deliver on time. Uber Freight works with 1 in 3 Fortune 500 shippers across North America and manages over $17B in freight. Learn more at www.uberfreight.com.
Candidate Privacy Notice
Uber Freight is committed to protecting the privacy of our candidates. We collect and process personal data in accordance with applicable data protection laws. For detailed information on how we handle candidate data, please review our Candidate Privacy Notice.
EEOC
Uber Freight is proud to be an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regards to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.
For California-based roles: The salary range for this role is $183,000.00 - $223,200.00 per year
Skills Required
- Bachelor's degree in Computer Science, Computer Engineering, or related fields
- At least 5+ years of Software Engineering or ML Engineering experience
- Experience in one or more programming languages including Python, Go or Java
- Proven experience with designing and implementing machine learning models in production environments with large data sets
- Experience in communicating algorithm choices, ML system design & concepts to leadership, technical peers & industry experts
- Strong adherence to metrics driven development, with a disciplined and analytical approach to product development
- MS or PhD degree in Computer science, Data Science, ML or equivalent practical experience
- Deep understanding of ML theory and a broad toolkit of algorithms, including deep learning, instance-based learning, and traditional statistical models
- Experience with designing and implementing machine learning models in production environments applied to generative AI, applications of large language models
- Experience in stream processing (Storm, Spark, Flink) and graph processing technologies
Uber Freight Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Uber Freight and has not been reviewed or approved by Uber Freight.
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Healthcare Strength — Health coverage is considered strong, including medical, dental, vision, and mental-health/EAP options with HSA/FSA support. This is often highlighted as a reliable cornerstone of the package.
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Parental & Family Support — Parental leave stands out with extended paid time for new parents and broader family-planning support. This category is frequently singled out as a clear strength.
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Leave & Time Off Breadth — PTO and sick leave are described positively, with hybrid/remote flexibility in many roles supporting work–life balance. Time-off policies are seen as a meaningful contributor to overall satisfaction even when pay sentiment is mixed.
Uber Freight Insights
What We Do
Powering Intelligent Logistics
