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Code Metal is an automated software engineering platform that uses AI and formal verification methods to produce provably correct code. The company specializes in transpilation between different languages and bridging the gap between algorithm development and deployment to embedded systems. Customers include the U.S. Air Force, L3Harris, RTX, and Toshiba.
You will join the hardware engineering team to architect and expand capabilities for creating production-ready RTL (Register Transfer Level) from high-level algorithm descriptions. This role focuses on HLS (High-Level Synthesis) integration and RTL code generation, working with a team that values technical rigor, ownership, and cross-disciplinary collaboration.
Key responsibilities include:
- Develop C++ and post-HLS readability and optimization passes to produce human-auditable RTL
- Leverage agentic AI and verification capabilities within Code Metal's platform
- Contribute to CI/CD qualification including automated RTL simulation, functional verification, and regression testing
You will work in a hybrid arrangement with flexibility between Boston and remote work, with relocation assistance available for qualifying candidates.
REQUIREMENTS:
- 3+ years of hands-on experience writing RTL code or using High-Level Synthesis, including at least one commercial HLS tool (Catapult, Vitis HLS, Stratus, or equivalent)
- Solid hardware modeling background regarding fixed-point arithmetic, bit-accurate types, synthesis pragmas, and modeling trade-offs
- Scripting experience in Python for development, toolchain automation, and testing
- Strong debugging and problem-solving skills
- Experience with simulation and functional verification flows
PREFERRED QUALIFICATIONS:
- Experience with Linux-based development environments
- Solid understanding of RTL / VHDL
- Understanding of FPGA architectural capabilities and constraints
- Knowledge of verification methodologies and testbench development
- Experience with DSP algorithms and applications using Python/MATLAB
- Interest in or familiarity with LLM-assisted code transformation and readability tooling
- Experience with Git-based development workflows and CI/CD environments
