Senior Hardware Engineer (Computer Architecture and Chip Design), AI Training Expert (PhD)

About the role
Cobalt builds expert data and evaluation infrastructure for AI developers. We are recruiting senior hardware engineers and computer architects for a contract project that tests whether frontier AI models can carry out real hardware design and verification work in a command line environment. Your job is to design original, realistic hardware tasks that a leading AI model fails to solve.
What you will do
Design self-contained command line tasks drawn from real hardware engineering work, such as finding and fixing a functional bug in a Verilog or SystemVerilog design, writing a testbench that exposes a subtle corner case, repairing a design that fails timing or synthesis, proving or disproving a property with formal verification, debugging a pipeline hazard or cache coherence problem in a processor model, evaluating an architectural trade-off in a simulator, and bringing up bare-metal firmware on an emulated processor.
Build the task environment using open-source tools, write a reference solution, and write automated tests that verify whether a solution is correct, for example through simulation against a reference model.
Test your task against a frontier AI model and refine it until the model fails for substantive reasons rather than because of ambiguity or trick wording.
Respond to reviewer feedback until the task is accepted.
Who we are looking for
A PhD in electrical engineering, computer engineering, computer science, or a closely related field.
Academic or industry experience in computer architecture, digital design, design verification, or a closely related area of chip development.
At least one publication, either academic (for example a peer-reviewed paper at a recognized architecture or design automation venue) or professional (for example a conference talk, a granted patent, or a widely used open-source hardware project).
Expert-level skill in Verilog or SystemVerilog, and working knowledge of C or C++ and Python.
Familiarity with open-source hardware tools, such as Verilator, Icarus Verilog, Yosys, gem5, or the RISC-V toolchain and QEMU. Experience with commercial tools transfers well, but tasks must be built with open-source tools only.
Fluency in the Linux command line, shell scripting, Docker, and Git.
The ability to write precise task specifications that another engineer could follow without asking questions.
Why Cobalt AI:
Advance frontier AI where it counts. Apply your research expertise to the data that frontier labs cannot obtain any other way, where your reasoning directly shapes how the next generation of models works through technical problems.
Grow professionally. Expand your influence through evaluation projects, advisory roles, and research collaborations, while deepening your understanding of how frontier models are trained and assessed.
Work with a top-tier network. Collaborate with researchers from leading institutions and labs on high-impact, flexible work.
Set your own schedule. Flexible 10 to 40 hour weeks that fit around your research position and your life.
Competitive pay. Rates vary by project and are determined by a number of factors, including scope, skillset, and experience.

Work arrangement
No