Applied AI Engineer, Top Hardware Priorities
Core
Build applied AI workflows and agentic systems to automate hardware and software engineering tasks like optimization, verification, debugging, and simulation.
Role type
Senior Applied AI Engineer (Hardware-adjacent)
Builds
AI-assisted engineering tools, agent loops, validation harnesses, and automation platforms for hardware design and software optimization.
Domain
Semiconductor hardware engineering and AI systems
Deliverable
production ML models
Required skills
Python, C++, C, HIP, CUDA, Rust, applied AI, agentic systems, debugging, root-cause analysis, hardware design workflows, GPU/CPU performance engineering, LLM agents, tool use, retrieval
Preferred skills
RTL/Verilog/SystemVerilog, formal verification, EDA tools, compiler tooling, ROCm/HIP, experiment tracking, RL, post-training methods
Technologies
Python, C++, C, HIP, CUDA, Rust, LLMs, compilers, simulators, formal checks, profilers, benchmark harnesses, ticket systems
Responsibilities
Build applied AI workflows for optimization, verification, debugging, simulation, and automation; Convert manual processes into structured tasks with validation and scoring; Partner with domain owners to define success metrics; Develop tools for AI agents to use engineering systems; Build human-in-the-loop workflows; Improve model performance via prompts and evaluation datasets; Generalize patterns into reusable platforms and dashboards.
Seniority
Senior, hands-on IC
