Technical Program Manager, AI Research Engineering

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We are seeking a Technical Program Manager to drive execution across AI Research Engineering, Applied AI, ML Systems, and AI/ML Platform teams. This role will coordinate programs spanning AI/ML workflows, reinforcement learning, inference, evaluation infrastructure, agentic/recursive self-improvement systems, and shared platforms supporting hardware and software optimization, verification, simulation, and performance engineering. THE PERSON: This is a hands-on TPM role for someone who can translate complex technical strategy into clear execution plans and work credibly with ML engineers, AI engineers, platform engineers, research scientists, and hardware/software domain experts.

Lead planning and execution of complex, cross-functional AI/ML and engineering programs, including milestones, dependencies, resources, risks, and critical paths. Translate ambiguous technical goals into structured plans, workstreams, success metrics, and acceptance criteria. Align engineering, research, platform, and hardware/software teams on priorities, scope, and delivery. Establish execution rhythms, track milestones and blockers, and provide clear executive-level status reporting. Coordinate platform and AI workflow initiatives involving benchmarking, evaluation, experiment tracking, distributed training/inference, and automation. Track measurable outcomes such as performance, correctness, regression rates, adoption, experiment throughput, and infrastructure utilization. Drive pilot and production readiness, including rollout plans, documentation, support, and retrospectives. Identify recurring delivery bottlenecks and drive improvements to processes, staffing, and technical roadmaps. Technical Focus AI/ML systems, agentic AI, RL, inference, and evaluation Distributed ML infrastructure and GPU platforms AI-driven engineering workflows and automation Hardware/software optimization, RTL, verification, simulation, firmware, compilers, and performance engineering Moving research prototypes into reliable, production-oriented engineering systems REQUIRED QUALIFICATIONS: Strong experience in Technical Program Management, Engineering Program Management, or equivalent within complex software, AI/ML, or engineering environments. Strong technical fluency in AI/ML systems, software engineering, distributed systems, or ML infrastructure. Proven ability to manage multiple complex workstreams with ambiguous requirements and shifting priorities. Excellent communication skills with engineers, researchers, technical leaders, and executives. Strong skills in program planning, dependency management, risk management, milestone tracking, and executive-level status reporting.

Experience with AI/ML, ML systems, developer platforms, or internal AI tooling. Familiarity with GPU computing, CUDA/ROCm/HIP, distributed training/inference, Kubernetes, Ray, or Slurm. Experience in semiconductor, EDA, verification, firmware, compilers, or HPC. Experience with agent frameworks, LLM tool use, benchmark automation, experiment tracking, or evaluation platforms. Experience bridging research prototypes and production engineering systems. Experience operating in matrixed, cross-functional organizations. ACADEMIC CREDENTIALS: Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, or related field, or equivalent practical experience.