What are the responsibilities and job description for the Staff Software Engineer AI Data position at Jobs via Dice?
About The Role
Uber's next generation of AI is built upon its real-time nervous system-a platform that processes billions of critical messages for everything from ETAs to driver-rider communications. Our team's mission is to transform this vast stream of data into the core knowledge that powers intelligent, autonomous agents across the business.
We're seeking a foundational Staff Machine Learning Engineer to pioneer Uber's next generation of AI. As the key technical leader, you will architect and build a self-evolving platform from the ground up, translating vast, real-time data into a central knowledge base to power intelligent, autonomous agents. This role is for a visionary engineer who thrives in ambiguous, \"0-to-1\" environments and is passionate about building novel, large-scale AI systems with a direct global impact.
\\- What the Candidate Will Do ----
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 [](;br>
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](;br>
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.
Uber's next generation of AI is built upon its real-time nervous system-a platform that processes billions of critical messages for everything from ETAs to driver-rider communications. Our team's mission is to transform this vast stream of data into the core knowledge that powers intelligent, autonomous agents across the business.
We're seeking a foundational Staff Machine Learning Engineer to pioneer Uber's next generation of AI. As the key technical leader, you will architect and build a self-evolving platform from the ground up, translating vast, real-time data into a central knowledge base to power intelligent, autonomous agents. This role is for a visionary engineer who thrives in ambiguous, \"0-to-1\" environments and is passionate about building novel, large-scale AI systems with a direct global impact.
\\- What the Candidate Will Do ----
- Architect the Platform: Lead the technical design of the end-to-end system for data ingestion, knowledge extraction, and action generation.
- Build the \"Data to Knowledge\" Pipeline: Implement robust, scalable systems for generating contextual embeddings and constructing a dynamic knowledge graph from diverse, real-time data sources.
- Develop Self-Evolving Systems: Design and integrate online learning and reinforcement learning models to ensure the platform continuously adapts and improves.
- Drive Technical Decisions: Own the critical decisions on frameworks, models, and infrastructure needed to bring ideas to production.
- System Building Experience: 8 years of experience designing, building, and shipping production AI/ML systems at scale. Specific experience with agentic systems, search/recommendation platforms, or data-intensive applications is highly desirable.
- LLM & Foundation Models: Deep hands-on experience with Large Language Models. This includes fine-tuning, retrieval-augmented generation (RAG), Context Engineering, Prompt Engineering, and deploying models for real-world applications.
- Agent & Tooling Expertise: Proven experience in building systems that enable AI agents to reason, plan, and use external tools (APIs, databases).
- Technical Proficiency: Expert-level proficiency in Python and technologies for large-scale data processing (e.g., Spark, Flink, Ray).
- Familiarity with building ML platforms or infrastructure.
- Direct experience with knowledge graphs.
- Contributions to open-source AI/ML projects or publications in relevant fields.
- Experience with reinforcement learning or online learning systems.
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 [](;br>
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](;br>
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.
Salary : $223,000 - $248,000
