Bring your machine learning expertise to Uber’s Delivery Marketplace team and help shape the next generation of dispatch intelligence. This onsite role in Sunnyvale, CA focuses on designing, building, and productionizing advanced ML models and matching algorithms that support better ETA, pickup optimization, and trip reliability.
You’ll lead technical strategy and roadmap ownership, taking models and optimization systems from concept through large-scale deployment. You’ll also develop transformer-based models that generate embeddings and natural language profiles used across Marketplace use cases.
What you’ll do
- Own technical strategy and execution across multiple quarters, including platform-level architecture decisions, executive communication and alignment, technical mentorship, and cross-team technical influence
- Build novel online marketplace products that combine machine learning for prediction and forecasting with optimization to improve both business efficiency and user experience
- Drive end-to-end design, development, and productionization of ML solutions for large-scale distributed systems serving billions of trips
- Develop transformer-based models using pre-training and fine-tuning to produce embeddings and natural language profiles that power Marketplace applications
What you’ll need
- Ph.D., M.S., or Bachelor in Computer Science, Mathematics with a focus on Machine Learning, or an equivalent technical background with exceptional demonstrated impact
- 3+ years experience leading development and deployment of ML models in large-scale production environments at top-tier ML companies (example scale: 1M+ predictions/sec or 100M+ users), with a track record of delivering business impact over multiple quarters
- Proficiency in Python, Scala, Java, or Go
- Proficiency with large-scale data systems (such as Spark or Ray), real-time processing (such as Flink), and microservices architectures
- Experience in developing, training, productionizing, and monitoring ML solutions at scale, from offline pipelines to online serving and MLOps
- Deep understanding of modern ML algorithms
Tools you may work with
Python, Scala, Java, Go, Spark, Ray, Flink, microservices architectures, machine learning and deep learning, causal modeling, reinforcement learning, transformer-based models, embeddings, natural language profiles, and MLOps.
Preferred qualifications
- Experience developing and deploying ML models for large-scale business problems
- Track record translating complex business problems into technical solutions and driving cross-functional projects
- Excellent communication skills to lead initiatives across multiple product areas
- Proficiency in deep learning, causal machine learning, or reinforcement learning
- Proficiency with large embedding and language models
Compensation and benefits
Salary range: USD 202,000 - 224,000 per year (base). Eligible to participate in Uber’s bonus program, and may be offered an equity award and other types of compensation.
- Full-time employees are eligible to participate in a 401(k) plan
- Eligible for various benefits
Office location and work expectations
Offices remain key to collaboration and Uber’s culture. Unless approved for full remote work, employees must spend at least 50% of their time in-office.
