About the Role

At Uber, we reimagine the way the world moves for the better. There are several operations and technologies that enable this mission and Uber AI Solutions (aka Global Scaled Solutions) organization leads many of those capabilities such as data annotation for AI/ML innovation, app testing, localization/internationalization, map editing, data analytics, engineering and more. We combine technology and human intelligence optimally to run scaled programs.

At Uber AI Solutions, we deliver high quality scaled programs in operations, technology and data analytics for various Uber businesses, leveraging our deep vendor partner network capabilities to carry out the program execution. We are also extending our impact and reach beyond Uber - our tech+ops solutions coupled with Uber's strength of building a platform for flexible work will enable enterprises world-wide to accelerate their data, AI and product journeys. While we do this, we look forward to creating flexible earnings opportunities through online tasks for millions of people across the world. Together, our tech, operations expertise and platform for knowledge work are uniquely positioned to be the best-in-class human in the loop solution for the industry.

We are looking for an exceptional candidate to lead program delivery and client engagement in the domain of AI training and evaluations - specifically for coding/engineering, agentic AI, data analytics and related fields - in the Engineering Services team of Uber AI Solutions. This is an opportunity for the candidate to build and scale the customer mindshare and impact for coding and data use cases in AI training (for foundational LLMs, agentic AI etc) at Uber AI Solutions, and establish us as a leader in the data annotation and AI training marketplace.

What the Candidate Will Do:

Client engagement for presales support - partner with Sales to interact with prospective clients (AI labs, foundation LLM companies, agentic AI companies, others) to shape the project scope, evangelise our capabilities, design the delivery solution, and governance approach. Demonstration of a deep understanding of this space during client engagement is a key requirement
Client engagement for program delivery - represent the service delivery organization (located globally with a predominant India/offshore footprint) and collaborate with them in order to drive ongoing governance, enable troubleshooting, find up/cross sell opportunities, bring thought leadership with client teams
Program delivery - help to manage US/onshore based delivery of annotation / training/ evaluation of AI/LLM/ML for coding and data areas, where required
Innovation and thought leadership - demonstrate deep understanding and expertise of coding and data analytics related AI training/evals including agentic AI (e.g., opportunity identification, model performance benchmarking) with prospective clients; leverage this expertise to drive talent supply strategy, tech platform and tooling, and any other relevant new capabilities to advance the capability and maturity of this area
Sourcing strategy and implementation inputs - collaborate with our Supply team to help source and develop worker pools in the US/onshore with technical expertise for coding and data related training/evals
Tech platform capability and roadmap inputs - collaborate with our Product and Engineering teams to help develop a roadmap for tech and tooling required specific to coding and data analytics related tasking
Stakeholder management - represent the coding and data AI capabilities at senior leadership level interactions and forums, evangelise our capabilities, drive sponsorship and backing for initiatives
Best practices - continually improve ways of work, enhance delivery maturity, elevate governance and impact

Basic Qualifications:

7+ years of overall experience, with specific familiarity in software engineering, ML engineering, ML ops domains
Familiarity and experience in leading or managing client interactions (i.e., AI labs, foundation LLM companies, agentic AI companies) for data annotation, training, evaluation, performance benchmarking in the area of coding and development for foundational AI/LLM/ML is required. Familiarity with the same for data analytics, ML, agentic AI disciplines additionally is a plus
Experience in client facing service delivery management, solutioning, governance - with external client stakeholders at senior levels and/or their AI teams
Familiarity with strategies for delivery and QC processes in this domain is required
Track record of driving innovation and thought leadership in AI/ML/LLM training and evaluation services - e.g., via model benchmarking, opportunity identification based on emerging AI industry trends
Strong ability to communicate, bring clarity of thought in messaging for senior management as well as broader teams
Strong collaboration skills and abilities - working across silos and team structures to drive impact effectively
Ability to work in a global organization across locations and time zones

Preferred Qualifications:

Education in technical domains like engineering, STEM, business management
Deep knowledge of AI domain - generative AI, agentic AI, LLMs, ML ops - with a curious bent of mind to keep updated on, and participate in, latest developments and research
Strong business acumen, willingness to take smart risks and grow
Ability to get hands-on and go deep and be very detail oriented where needed, and zoom out to see and manage the big picture
Sense of ownership - self starter who can take a charter and define goals, execute plans
Good prioritization and time management skills

For San Francisco, CA-based roles: The base salary range for this role is USD$162,000 per year - USD$180,000 per year. For Sunnyvale, CA-based roles: The base salary range for this role is USD$162,000 per year - USD$180,000 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.

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