TLM, Multimodal Infrastructure

The TLM at OpenAI's Multimodal Infrastructure team is responsible for leading a high-caliber team of ML infrastructure engineers. This includes driving the technical direction for multimodal research initiatives, collaborating closely with researchers and engineers, and designing, building, and operating software systems for training and evaluating ML models on complex multimodal data.

To apply for the TLM position at OpenAI, you need strong software engineering skills, experience in building high-performance infrastructure, and an understanding or eagerness to learn about ML systems, particularly those involving large-scale training or multimodal data. Experience with model training infrastructure is highly desirable.

OpenAI is dedicated to the growth of its engineers, especially in the TLM role. As a TLM, you will provide mentorship, encourage innovation, and support your team's development. Collaborating on diverse multimodal projects also enables team members to learn and grow in a cutting-edge environment.

OpenAI fosters a collaborative and inclusive work culture, particularly for those in the TLM position. You'll engage with talented individuals across various fields, push the boundaries of AI together, and contribute to high-impact projects in a supportive environment. The hybrid work model also adds flexibility to how you work.

Yes, OpenAI offers relocation assistance for the TLM position. This benefit helps new employees transition smoothly to our San Francisco location, ensuring they feel welcomed and supported from day one as they join the Multimodal Infrastructure team.

When discussing your experience in leading a tech team, focus on specific projects where you played a crucial role. Highlight how you managed team dynamics, dealt with challenges, and ensured that projects met timelines and technical requirements, especially in the context of machine learning.

To effective collaborate with researchers and engineers, emphasize your communication skills and ability to understand both technical and research perspectives. Share examples where you successfully bridged gaps between teams, prioritizing outcomes and fostering teamwork.

When answering this, detail a specific instance, including the challenges you faced while working with complex, high-volume data and the innovative solutions you implemented for system design. Discuss the outcomes to showcase your capabilities.

In your response, highlight strategies that involve effective communication with your team to assess project impact, urgency, and resource needs. Explain how these strategies contribute to maintaining focus on key tasks and achievable milestones over time.

Discuss your experience with performance optimization techniques, including any tools or methodologies you’ve implemented in previous roles. Explain how you measure success through performance metrics and continuous monitoring.

Address the unique challenges of multimodal systems, such as data integration, model training, and the need for efficiency. Your insights demonstrate your readiness to navigate these complexities, an essential quality for a TLM at OpenAI.

Be prepared to share specific examples that illustrate your cross-functional leadership capabilities—how you engaged with various departments, resolved conflicts, and created synergies that led to successful outcomes in projects.

Your answer should reflect a genuine interest and commitment to continuous learning. Mention your use of industry resources, conferences, journals, or specific communities where you actively participate to stay aware of emerging ML technologies.

Share your personal motivation and the impact you believe AI can have on society. Discussing your passion for leveraging technology to solve global challenges helps interviewers understand your alignment with OpenAI's mission.

When addressing underperformance, it's vital to articulate your approach to constructive feedback, setting clear performance metrics, and fostering an open dialogue that encourages improvement, all while supporting the team member’s professional development.