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Internship Uber Customer Service Jobs (Flexible Options) Near Me

Tchibo GmbH

... Über eingehendes Feedback behältst du den Überblick und hast stets einen Blick für Trends sowie ... Eng verzahnt arbeitest du mit Customer Service, Product Ownern und weiteren Schnittstellen zusammen ...

PAM Transport

Customer Service Intern

Tontitown, AR · On-site

PAM Transport Internship Opportunities Join us for an exciting opportunity to be part of a team ... Providing customer service to various large accounts * Implementing safety and risk management

PAM Transport

Customer Service Intern

Tontitown, AR

Our internship program offers a fully immersive, multi-faceted experience within the Supply Chain ... Providing customer service to various large accounts * Implementing safety and risk management

PAM Transport

Customer Service Intern

Tontitown, AR · On-site

Our internship program offers a fully immersive, multi-faceted experience within the Supply Chain ... Providing customer service to various large accounts * Implementing safety and risk management

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Staff Machine Learning Engineer, Core Services Eng (GenAI)

Uber Technologies, Inc.

San Francisco, CA • On-site, Remote

Full-time

Retirement

Re-posted 24 days ago

Uber rating

6.8

Company rating: 6.8 out of 10

Based on 114 frontline employees who took The Breakroom Quiz

4th of 9 rated taxi private hire

Job description

About the Role

Uber's Customer Obsession team builds the platform and AI that powers worldclass support across mobile, web, and voice at global scale. We are now hiring a Staff ML Engineer to architect, productionize, and scale an autonomous support agent that resolves customer issues endtoend. Experience with agentic architectures is a major plus. 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 you will do

  1. Own the endtoend agent architecture: agentic planning and execution loops, long-term memory, persona/voice, knowledge routing, and policy enforcement for compliant, onbrand conversations.
  2. 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.
  3. 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.
  4. 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.
  5. Mentor/principlelead multiple pods; set technical strategy and quality bars; coach senior engineers on agentic patterns, reliability, and experiment velocity.


Basic Qualifications

  1. 7+ years building production ML/AI systems; 2+ years leading complex ML initiatives endtoend.
  2. Deep expertise in LLMdriven systems (inference optimization, prompt/program design, finetuning, distillation/LoRA, safety/guardrails, evals).
  3. Track record of shipping customerfacing intelligent experiences with measurable impact (A/B testing, metrics literacy).
  4. Bachelor's Degree, or above, in Comp Science or related field.


Preferred Qualifications

  1. Agentic architectures in production (planner/executor, memory, multistep reasoning) and RAG over complex, policyheavy knowledge bases.
  2. Experience building support automation for large consumer platforms (routing, policy codification, internal tooling, copilot/autoresolve).
  3. Multilingual NLU/NLG (codeswitching, lowresource languages), hallucination mitigation, safety redteaming, and privacybydesign.
  4. Practical expertise balancing speed and reliability at scale: experiment frameworks, feature flags, canary/guarded rollouts, and clear killswitches.
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Ready to Ride?


This isn't the kind of place where you follow a playbook - it's where you help write one. If you're driven by impact, energized by challenge, and ready to shape how the world moves - we'd love to hear from you.


You may be eligible for bonuses, equity, and other compensation, as well as a range of benefits. Explore our benefits.


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. Some roles, like those at greenlight hubs, require full-time in-office presence. Ask your Recruiter for details about this role's requirements.


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.

For San Francisco, CA-based roles: The base salary range for this role is USD $232,000 per year - USD $258,000 per year.


For Sunnyvale, CA-based roles: The base salary range for this role is USD $232,000 per year - USD $258,000 per year.


For all US locations, 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.

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