Software Engineer II - Machine Learning

About the Role

The NOVA AI team builds the platform and AI that powers world‑class support across mobile, web, and voice at global scale. We are now hiring a Senior ML Engineer to build and scale an autonomous support agent that resolves customer issues end‑to‑end. You’ll push the state of the art in GenAI for customer service—LLM orchestration, evaluation, safety guardrails, multilingual support—while holding a very high bar for reliability and cost efficiency. We are still at an early stage and value candidates with bias for action who get creative with GenAI tools to accelerate execution and experimentation.

What the Candidate Will Need / Bonus Points

---- What the Candidate Will Do ----

1. Work on agent architecture: agentic planning and execution loops, long-term memory, persona/voice, knowledge routing, and policy enforcement for compliant, on‑brand conversations.
2. Ship production systems that handle millions of conversations with rigorous SLOs, fallbacks, and canaries; design graceful degradation (e.g., human handoff) and safety guardrails (prompt‑injection, jailbreak, PII redaction).
3. Advance retrieval & reasoning: Build next-generation retrieval and reasoning pipelines, where the agent can search across different knowledge sources, apply policy-driven tools, and call structured workflows and ensure that responses are consistently grounded.
4. Establish evals that matter: offline rubrics, simulated scenarios, safety tests, cost/latency tradeoff suites, and LLM‑as‑judge (with calibrated human review) wired into CI/CD and experiment platforms.
5. Drive automation at scale: partner with Product/Design/Operations on coverage, policy alignment, localization, and rollout strategy to better customer experience and reduce cost per contact.

---- Basic Qualifications ----

1. Background in LLM‑driven systems (inference optimization, prompt/program design, fine‑tuning, distillation/LoRA, safety/guardrails, evals).
2. Strong software engineering in Python
3. Bachelor's degree (or above) in Computer Science or related field

---- Preferred Qualifications ----

1. Agentic architectures in production (planner/executor, memory, multi‑step reasoning) and RAG over complex, policy‑heavy knowledge bases.
2. Experience building support automation for large consumer platforms (routing, policy codification, internal tooling, co‑pilot/auto‑resolve).
3. Multilingual NLU/NLG (code‑switching, low‑resource languages), hallucination mitigation, safety red‑teaming, and privacy‑by‑design.
4. Practical expertise balancing speed and reliability at scale: experiment frameworks, feature flags, canary/guarded rollouts, and clear kill‑switches.

For Sunnyvale, CA-based roles: The base salary range for this role is USD$171,000 per year - USD$190,000 per year.

You will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. More details can be found at the following link https://jobs.uber.com/en/benefits.

Uber's mission is to reimagine the way the world moves for the better. Here, bold ideas create real-world impact, challenges drive growth, and speed fuels progress. What moves us, moves the world - let's move it forward, together.

Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form.

Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.