- Company Name
- Uber
- Job Title
- Senior Machine Learning Engineer - Marketplace Pricing
- Job Description
-
**Job Title**
Senior Machine Learning Engineer – Marketplace Pricing
**Role Summary**
Lead the design, development, and productionization of advanced machine learning models and pricing algorithms that power real‑time marketplace pricing for a large‑scale, multi‑objective system. Drive measurable business impact, mentor junior engineers, and set technical direction for high‑volume, real‑time predictions.
**Expectations**
- Deliver end‑to‑end ML solutions that serve billions of trips and 1M+ predictions per second.
- Translate ambiguous business challenges into scalable, data‑driven pricing strategies.
- Own the entire lifecycle from model research to deployment, monitoring, and continuous improvement.
- Mentor and collaborate with engineers, product managers, and scientists across the organization.
**Key Responsibilities**
- Design and implement ML models (deep learning, causal inference, reinforcement learning) for dynamic supply pricing.
- Develop novel pricing algorithms that combine ML, algorithmic game theory, and mathematical optimization.
- Build and maintain large‑scale data pipelines (Spark, Ray) and real‑time processing systems (Flink).
- Deploy and monitor ML solutions in a microservices architecture, ensuring reliability, latency, and scalability.
- Lead technical discussions, set project scope, and influence cross‑functional decisions.
- Provide mentorship to junior engineers and contribute to the team’s technical growth.
- Present performance metrics and business impact to executive stakeholders.
**Required Skills**
- Programming: Python, Scala, Java, or Go.
- Big Data & Real‑Time: Spark, Ray, Flink; microservices architectures.
- MLOps: model training, deployment, monitoring, CI/CD for ML.
- ML Expertise: DNNs, multi‑task learning, transformers, causal ML, reinforcement learning.
- Optimization: Linear programming, convex optimization, algorithmic game theory.
- Strong analytical skills and ability to translate business objectives into technical solutions.
**Required Education & Certifications**
- Ph.D., M.S., or B.S. in Computer Science, Machine Learning, Operations Research, or equivalent technical discipline.
- Minimum 4+ years of experience deploying production‑grade ML models and optimization algorithms that deliver measurable business impact.