Program Manager II, Gen AIOps

About the Role

Uber AI Solutions is one of Uber's biggest bets with the ambition to build one of the world's largest data foundries for AI applications and evolve into a platform of choice for a variety of online tasks. Data Labelling operations is one of the core functional teams within Uber AI Solutions with the responsibility to oversee the end-to-end lifecycle of the data annotation programs for B2B clients. At its core, our ability to build industry-leading data annotation programs is our right to win in this space.

As a seasoned program manager for data labeling in the Gen AI space, you will be responsible for defining the programs and its key objectives to support LLM model training. You will drive cross-functional efforts across Operations, Product, Engg and Legal to define the Program-level Ops strategy, define scalable data labeling workflows leveraging internal tools, external vendors, and automation.

1. Define the key objectives for data labeling projects to support generative AI initiatives. Partner with stakeholders (Sourcing, Engagement, Data Scientists, Machine Learning Engineers, and Product Managers) to identify data requirements and success criteria.
2. Drive daily, weekly, and monthly meetings internally with the partner teams and externally with the customer. Design scalable data labeling workflows that leverage internal tools, external vendors, and automation.
3. Optimize workflows for efficiency, accuracy, and cost-effectiveness, incorporating active learning and pre-labeling techniques where appropriate. Engage and manage relationships with data labeling vendors, ensuring timely delivery and adherence to quality standards.
4. Collaborate with cross-functional teams to align labeling efforts with broader AI model development timelines. Implement robust quality assurance processes to validate labeled datasets against gold standards.
5. Use metrics such as inter-annotator agreement, precision/recall, and throughput to monitor quality and make improvements.
6. Forecast resource requirements and ensure efficient allocation to meet deadlines. Advocate for inclusive and unbiased labeling practices to mitigate bias in AI models.

1. 5+ years experience managing scaled operations programs with 1+ year experience in GenAI / model training. Experience working in a fast-paced, ambiguous work environment.
2. Strong knowledge of machine learning concepts, particularly around supervised learning and training data needs.
3. Experience working with data annotation platforms and tools. Proven track record of managing large-scale projects with cross-functional teams and external vendors.
4. Excellent written and verbal communication skills, with the ability to influence technical and non-technical stakeholders.
5. Experience in Generative AI, including text, image, video or audio data labeling. Familiarity with active learning, semi-supervised labeling, and human-in-the-loop systems.
6. Strong understanding of ethical AI and best practices for minimizing dataset bias. Strong understanding of the gig economy landscape, freelancer behaviors, and recruitment strategies.