About the Role
We are the Workforce Experience Engineering (WEE) team. Our mission is to build state-of-the-art applications and integrations that deliver the next generation of employee experiences. This role will combine software engineering with AI product thinking to deliver best-of-breed productivity and business value.
---- What the Candidate Will Do ----
Our team is establishing the framework for developing and enhancing internal products powered by large language models (LLMs). We seek a talented Staff Software Engineer with expertise in Generative AI and natural language processing/understanding (NLP/NLU), emphasizing building a scalable, reusable, and extensible software product. Ideal candidates will have a background in software engineering with experience in language model evaluation, LLM alignment, synthetic data generation, LLM fine-tuning, retrieval-augmented generation (RAG), and multimodal modeling.
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You will help lead Generative AI initiatives by identifying transformative opportunities, researching the latest techniques in developing applications that are adaptable to future generations of AI models, guiding our teams through the entire AI development process, and collaborating with cross-functional stakeholders to deliver AI solutions into production that deliver substantial business value.
---- Basic Qualifications ----
- PhD or equivalent experience in Computer Science or related field AND 5+ years Software Engineering work experience OR 8+ years Software Engineering work experience.
- 8+ years of hands-on programming experience with at least one modern language, such as Go, Java, or Rust.
- 8+ years of experience contributing to the architecture and design of ML systems and tools.
- Strong sense of software design and usability of ML systems.
- Strong understanding of software engineering best practices, including version control, testing, CI/CD, and agile methodologies.
- Experience applying software engineering methodologies and best practices, including coding standards, code reviews, build processes, testing, software quality, and security.
- Experience in mentoring and guiding junior engineers.
---- Key Resonsibilities ----
- Design innovative methods, tools, and infrastructure to advance the capabilities of large language models and their real-world applications.
- Apply AI technologies to develop and optimize products and services across various domains.
- Contribute to the entire lifecycle of experiments, including designing and deploying experiments, writing scalable and reusable code, conducting rigorous evaluations, and systematically organizing and analyzing results.
- Collaborate effectively with a large, globally distributed team, contributing to shared goals and projects across time zones.
- Stay informed about the latest advancements in machine learning and Generative AI, incorporating cutting-edge research and techniques into practical applications.
- Mentor and guide other engineers, sharing knowledge and best practices in AI and machine learning.
- Ensure machine learning models' scalability, reliability, and efficiency in production environments.
- Engage in cross-functional collaboration with product managers, data scientists, and other stakeholders to translate business needs into AI-driven solutions.
- Continuously evaluate and improve existing models and systems, focusing on performance optimization and cost-effectiveness.
- Support on-call activities for critical issues.
For San Francisco, CA-based roles: The base salary range for this role is USD$218,000 per year - USD$242,000 per year.
For Sunnyvale, CA-based roles: The base salary range for this role is USD$218,000 per year - USD$242,000 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. You will also be eligible for various benefits. More details can be found at the following link https://www.uber.com/careers/benefits.
Uber is proud to be an Equal Opportunity/Affirmative Action 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.