Uber FreightRemote
Senior Software Engineer - Machine Learning
United States of America
Full Time
2 weeks ago
$152,000 - $186,000 USD
H1B Sponsor Likely
Key skills
Machine LearningGenerative AILarge Language ModelsPyTorchTensorFlowScikit-LearnSpark MLlibPythonGoJavaStream ProcessingStormSparkFlinkGraph ProcessingAIMLDeep LearningGenAIAgenticscikit-learnLeadershipPrototyping
About this role
Uber Freight is building a better future for shipping by creating innovative applications and models. As a Senior Software Engineer specializing in Machine Learning, you will develop high-impact solutions for Uber Freight’s marketplace and operations, focusing on predictive models and integrating Generative AI applications.
Responsibilities:
- 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
- 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
- Focus on optimizing logistics operations and network effects through core ML
- 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
Requirements:
- At least 5+ years of Machine Learning engineering experience
- Experience deploying ML models at scale using frameworks like PyTorch, TensorFlow, Scikit-Learn, or Spark MLlib
- 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
- Deep understanding of ML theory and a broad toolkit of algorithms, including deep learning, instance-based learning, and traditional statistical models
- BS, MS or PhD degree in computer science, Data Science, ML or equivalent practical experience
- 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
- Explain & communicate 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