Job description
We are looking for an experienced and highly motivated Engineering Manager to lead a dynamic team focused on machine learning algorithms or Large Language Model (LM) evaluation. In this role, you will guide a team responsible for the critical data and evaluation pipelines that ensure our models are accurate, robust, and performant. The ideal candidate will bring a strong mix of technical leadership, expertise in data curation and annotation processes, and deep analytical skills. You will collaborate closely with cross-functional research and engineering teams, requiring exceptional communication and strategic thinking. As the Engineering Manager for this team, you will be at the forefront of our AI/ML development lifecycle. Your day-to-day responsibilities will include:
- Team Leadership: Lead, mentor, and grow a team of engineers and data specialists. Foster a culture of innovation, rigorous analysis, and continuous learning.
- Evaluation Strategy: Define and execute the evaluation strategy for both CV and LM models. Build robust, scalable evaluation pipelines that accurately reflect real-world performance.
- Data Pipeline Management: Oversee the end-to-end data lifecycle. This includes establishing data curation guidelines, managing data quality, and optimizing large-scale annotation workflows with external vendors or internal teams.
- Analytical Deep Dives: Guide the team in performing rigorous data analysis to troubleshoot model regressions, uncover data quality issues, and identify opportunities for algorithmic improvements.
- Strategic Alignment: Act as the primary point of contact for your team, communicating progress, bottlenecks, and strategic data needs to leadership and partner teams.