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.
About The Role
We are looking for an exceptional candidate to develop and lead programs 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 existing capabilities 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 You Will Do
- Program delivery leadership - lead multiple annotation/training/eval programs for our clients (typically, various AI labs) for coding and data areas, with the scope including (but not limited to)
- Developing the delivery solution (skills, quality check methods, etc) based on the client requirements
- Source technical talent from our supply pools to fulfil the resource needs
- Manage the service delivery - quality checks, task flows (e.g., consensus based)
- Client stakeholder engagement for ongoing delivery
- Client engagement - partner with Sales to interact with clients (AI labs, foundation LLM companies, agentic AI companies, others) to shape the project scope, evangelise our capabilities, design the delivery solution, and governance during delivery. Demonstration of a deep understanding of this space during client engagement is a key requirement
- Sourcing strategy implementation - collaborate with our Supply team to source, develop, manage and maintain vendor relationships as well as crowd-sourcing channels to source and nurture worker pools with technical expertise for coding and data related training/evals
- Tech platform capability and roadmap - collaborate with our Product and Engineering teams to develop a roadmap for tech and tooling required specific to coding and data analytics related tasking; work closely with them to achieve the roadmap, drive platform adoption
- 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
- Team management - develop, coach and mentor the existing program manager team to build and scale the in-house talent for coding and data AI evals/training
- 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
- Culture champion - participate at org level overall, to drive organizational culture
---- What You Will Need----
- 10+ years of overall experience, with specific familiarity in software engineering, ML engineering, ML ops domains
- Familiarity and experience in leading or managing the delivery services 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 talent sourcing, talent supply development, tech/tooling, delivery and QC processes in this domain is required
- Familiarity with managing vendors, or experience working in a client-vendor setup
- Strong ability to communicate, bring clarity of thought in messaging for senior management as well as broader teams
- Track record of driving innovation and thought leadership in AI/ML/LLM training and evaluation services
- 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
- Ability to mentor and coach team members to build scale in the organization
