onsite
Senior Software Engineer - Machine Learning - Uber Freight
ML Engineer
Lead the design and deployment of scalable ML models for freight optimization, leveraging Python, TensorFlow, and AWS to deliver high‑performance solutions that drive smarter shipping decisions.
About the role
Key Responsibilities
- Architect, develop, and production‑grade deploy machine learning models that optimize routing, pricing, and capacity planning for freight operations.
- Collaborate with data scientists, product managers, and infrastructure teams to translate business requirements into robust ML pipelines.
- Implement end‑to‑end data workflows using Python, TensorFlow, and AWS services (SageMaker, S3, Lambda).
- Containerize models with Docker and orchestrate deployments on Kubernetes for high availability and scalability.
- Monitor model performance, conduct A/B testing, and iterate on feature engineering to maintain accuracy and relevance.
Requirements
- 5+ years of software engineering experience with a strong focus on machine learning.
- Proficiency in Python, TensorFlow or PyTorch, and experience building production‑grade ML pipelines.
- Hands‑on experience with AWS services (SageMaker, EC2, S3, Lambda) and container orchestration (Docker, Kubernetes).
- Strong problem‑solving skills and ability to work in a fast‑paced, collaborative environment.
- Excellent communication skills and a passion for delivering data‑driven solutions that impact real‑world logistics.
Skills
pythonmachine learningawstensorflowdocker