Daniel is an Engineering Manager with 11 years of experience who combines hands-on technical leadership with research-driven rigor, grounded by a PhD from MIT CSAIL and recent work as a Research Manager at FAIR. He excels at bridging advanced AI research and engineering execution, translating cutting-edge ideas into production-ready systems and guiding teams through complex technical trade-offs. Colleagues describe him as a pragmatic leader who mentors engineers while maintaining deep subject-matter expertise in machine learning research. His background suggests a knack for structuring research programs and operationalizing models at scale—skills that are especially valuable in teams looking to move from prototyping to reliable deployment.
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