Software Engineer II - Back-end & ML/AI Infra
Indexed description
What The Candidate Will Need / Bonus Points
---- What the Candidate Will Do ----
- As a Software Engineer II at Uber, you'll be working on code that's closest to the business.
- You will build user-facing products, handle and store thousands of transactions per second, and develop intelligent Privacy (Data Deletion) and Security(Access Control) strategies that scale.
- You will work on design, development and maintenance of services, frameworks, and solutions to support user-facing products, downstream services, or infrastructure tools and platforms used across Uber.
- You are passionate and pragmatic technologists who are able to design scalable systems while delivering efficient code.
- The privacy landscape is constantly evolving, and with the adoption of ML/AI backed by extensive heterogeneous data, security & privacy threats are inevitably broadened.
- With your deep and comprehensive expertise across major technology stacks, you will design, implement and scale industry-leading privacy solutions for the entire company.
- 4 years of professional industry experience and BS or MS in Computer Science or a related technical discipline, or equivalent practical experience.
- Proficiency in at least one of Go, Java, Python, or C++.
- Solid understanding of algorithms, data structures, and software engineering fundamentals.
- At least five years of software engineering experience
- Experience building or contributing to production backend or AI systems.
- Experience with GenAI, Model Context Protocol
- Experience developing backend or distributed systems such as microservices, APIs, or data-processing services.
- Familiarity with distributed systems concepts, including reliability, scalability, and performance trade-offs.
- Exposure to ML or AI systems, including model inference, data pipelines, or ML-enabled features.
- Interest or experience applying ML/AI techniques to security, privacy, or risk-related problems (e.g., data classification, PII detection, policy enforcement).
- Experience with system monitoring, observability, and production operations.
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