ChatGPT Jobs · 1 hour ago
Senior Machine Learning Engineer
Uber is a company that reimagines the way the world moves for the better. They are seeking a Senior Machine Learning Engineer to build and scale an autonomous support agent that resolves customer issues end-to-end, focusing on GenAI for customer service and ensuring high reliability and cost efficiency.
Computer Software
Responsibilities
Work on agent architecture: agentic planning and execution loops, long-term memory, persona/voice, knowledge routing, and policy enforcement for compliant, on-brand conversations
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)
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
Establish evals that matter: offline rubrics, simulated scenarios, safety tests, cost/latency tradeoff suites, and LLMasjudge (with calibrated human review) wired into CI/CD and experiment platforms
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
Qualification
Required
Background in LLM-driven systems (inference optimization, prompt/program design, finetuning, distillation/LoRA, safety/guardrails, evals)
Strong software engineering in Python
Track record of shipping customer-facing intelligent experiences with measurable impact (A/B testing, metrics literacy)
Bachelor's degree (or above) in Computer Science or related field
Preferred
Agentic architectures in production (planner/executor, memory, multistep reasoning) and RAG over complex, policy-heavy knowledge bases
Experience building support automation for large consumer platforms (routing, policy codification, internal tooling, copilot/autoresolve)
Multilingual NLU/NLG (code-switching, low-resource languages), hallucination mitigation, safety red teaming, and privacy by design
Practical expertise balancing speed and reliability at scale: experiment frameworks, feature flags, canary/guarded rollouts, and clear killswitches
Benefits
Eligible to participate in Uber's bonus program
May be offered an equity award & other types of comp
Eligible for various benefits
Company
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Funding
Current Stage
Early StageCompany data provided by crunchbase