Uber - Staff Software Engineer/Technical Lead - Machine Learning/Artificial Intelligence

About The Role :

This is a pivotal leadership role to redefine the future of search and knowledge access at Uber.

We are looking for a visionary Staff Engineer and Tech Lead to spearhead the evolution of our internal search platform, transforming it from a traditional information retrieval tool into a conversational, intelligent, and action-oriented experience.

Your primary mission will be to architect a world-class search ecosystem for all Uber employees.

This requires a dual-pronged technical strategy: leading the in-house development of novel AI components while also conducting deep evaluations of cutting-edge third-party solutions.

You will be the key technical decision-maker on when to build and when to integrate.

As a Tech Lead Manager, you will be responsible for the high-level technical architecture, the strategic roadmap, and the leadership of a talented team of engineers.

You will set the technical vision, mentor your team, and remain hands-on, architecting critical systems and integration points.

This is a unique opportunity to own the strategy for a mission-critical platform and leverage the entire AI landscape-both internal and external-to deliver profound impact.

What The Candidate Will Need / Bonus Points :

What the Candidate Will Do :

- Architect the Ecosystem : Design and own the technical vision for Uber's next-generation enterprise search platform, creating a cohesive strategy that integrates first-party AI models with best-in-class third-party technologies.

- Lead AI Implementation : Drive the exploration and implementation of advanced AI capabilities. This includes architecting conversational interfaces, enabling multi-step reasoning, and bringing agentic AI functionalities to our users, whether through in-house development or strategic integration.

- Make Critical Build-vs-Buy Decisions : Conduct deep technical evaluations of industry-leading AI solutions.

- You will own the process of vetting vendors, prototyping integrations, and providing clear recommendations to leadership.

- Lead and Mentor : Lead a world-class team of software and machine learning engineers.

- Provide technical guidance, conduct architectural reviews, and foster a culture of innovation and engineering excellence.

- Build and Integrate : Remain hands-on, writing production-quality code for critical custom components, integration layers, and core platform infrastructure.

- Collaborate and Influence : Work closely with senior leadership, product managers, and stakeholders across the company to define the roadmap and ensure your team's work aligns with Uber's strategic goals.

Basic Qualifications :

- Bachelor's degree in Computer Science, Machine Learning, a related technical field, or equivalent practical experience.

- 8+ years of professional experience in software engineering, with a proven track record of shipping complex.

- Strong programming proficiency in Python and experience with systems programming languages (e., Go, Java, C++).

- Significant experience in designing and building production systems leveraging machine learning, especially in Search, NLP, or Conversational AI.

- 2+ years of experience in a formal or informal technical leadership role, including mentoring engineers and setting technical direction for a team.

Preferred Qualifications :

- Master's or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field.

- Experience architecting systems that involve Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and vector databases.

- Demonstrated experience making strategic build-vs-buy decisions and integrating large-scale third-party software or SaaS platforms into a complex enterprise environment.

- Experience with the architecture of AI agentic systems or complex, multi-step LLM-powered workflows (either through building or integration).

- Expertise with both traditional search technologies (e., Elasticsearch) and modern semantic search paradigms.

- Excellent communication skills, with the ability to articulate complex technical trade-offs to diverse audiences and influence technical strategy at a senior level.

- A strong product intuition and a passion for creating user-centric AI experiences that solve real-world problems.