This role pays more than
77%
of similar roles. Most pay
$177,087–$231,150
— the shaded band above.
At the midpoint, this role pays about
$234k
versus about
$204k
for comparable roles.
Based on 240 similar postings.
Employer
About Amd
AMD (Advanced Micro Devices) is a semiconductor company that develops high-performance processors, graphics cards, and adaptive computing solutions for gaming, data centers, and embedded markets. Industry: Semiconductors
Amd currently has
394 open roles
on FindRole.
Listed pay typically runs
$164,000–$246,000
across 394 roles with salary data.
Technical Program Manager, AI Research Engineering will drive execution across the AI Research Engineering, Applied AI, ML Systems, and AI/ML Platform teams. This role involves translating complex technical strategies into structured plans, managing milestones, and coordinating cross-functional workstreams involving research scientists, engineers, and hardware experts. The position focuses on moving research prototypes into production-oriented systems while overseeing programs for reinforcement learning, inference, evaluation infrastructure, and agentic systems. Key responsibilities include tracking performance metrics, identifying delivery bottlenecks, and managing distributed training and inference workflows. Candidates should possess technical fluency in AI/ML systems, GPU platforms, and hardware/software optimization including RTL, verification, firmware, and compilers. Relevant tools and technologies include CUDA, ROCm, HIP, Kubernetes, Ray, and Slurm. The role addresses the challenge of scaling research into reliable infrastructure for distributed training and performance engineering.
What does a Technical Program Manager earn in California?
Median $197500 from 68 postings across 19 companies.
Lead planning and execution of cross-functional AI/ML programs including milestones, dependencies, resources, and risks.
Translate ambiguous technical goals into structured workstreams, success metrics, and clear acceptance criteria.
Align engineering, research, platform, and hardware teams on project priorities and scope.
Establish execution rhythms and provide executive-level status reporting on progress and blockers.
Coordinate AI workflow initiatives involving benchmarking, evaluation, distributed training, inference, and automation.
Track measurable outcomes such as performance, correctness, regression rates, and infrastructure utilization.
Drive pilot and production readiness including rollout plans, documentation, and retrospectives.
Identify delivery bottlenecks to improve processes, staffing, and technical roadmaps.
What we're looking for
Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or related field, or equivalent practical experience.
Experience in Technical Program Management, Engineering Program Management, or equivalent within complex software, AI/ML, or engineering environments (preferred).
Technical fluency in AI/ML systems, software engineering, distributed systems, or ML infrastructure (preferred).
Ability to manage multiple complex workstreams with ambiguous requirements and shifting priorities (preferred).
Experience with AI/ML, ML systems, developer platforms, or internal AI tooling (preferred).
Familiarity with GPU computing, CUDA/ROCm/HIP, distributed training/inference, Kubernetes, Ray, or Slurm (preferred).
Experience in semiconductor, EDA, verification, firmware, compilers, or HPC (preferred).
Experience with agent frameworks, LLM tool use, benchmark automation, experiment tracking, or evaluation platforms (preferred).
AI
LLM
ASIC
RTL Design
Simulation
Formal Verification
System Architecture
Scalable Infrastructure
Data Pipelines
Software Engineering
Program Management
Pre-silicon Workflows