C

Code Metal

Optimizes research code for edge deployment

Forward Deployed Engineer

Embedded EngineeringConfirmed live in the last 24 hours
Full-timeHybrid

About the Job

Requirements

  • Eligible to obtain and maintain a U.S. security clearance; some assignments may require an active Top Secret clearance.
  • Experience in software engineering, systems engineering, or applied algorithm development is preferred.
  • Programming ability in at least one of Python, C++, CUDA, MATLAB, VHDL, Verilog, or Rust is preferred.
  • Hands-on experience with GPU programming, FPGA development, embedded systems, or edge compute environments is preferred.
  • Experience working with compute-intensive workloads such as digital signal processing, radio frequency, communications, or computer vision is preferred.
  • Ability to optimize and deploy software on specialized or constrained hardware is preferred.
  • Ability to debug complex systems across software and hardware boundaries is preferred.
  • Experience delivering software or systems in defense, aerospace, industrial, or other mission-critical environments is preferred.

Responsibilities

  • Own end-to-end deployment of validated customer solutions, from implementation and integration through production acceptance, and deliver reliable working systems on target hardware.
  • Work directly with customer engineers and operators to integrate solutions into their environment, understand operational constraints, and close gaps between validated solutions and production use.
  • Productionize and optimize validated digital signal processing, radio frequency, communications, or other compute-heavy pipelines so they are reliable, performant, testable, and deployable on GPUs, FPGAs, and other accelerators using Code Metal's platform.
  • Profile, debug, and tune systems for latency, throughput, memory, and power across heterogeneous compute environments.
  • Identify and resolve issues spanning algorithms, software, hardware, and toolchains in complex deployment environments.
  • Partner with Solutions Engineers, Solutions Architects, product, and core engineering to resolve field issues, harden reusable capabilities, and feed deployment learnings into the platform.
  • Navigate ambiguity, unblock critical issues, and move deployments forward in high-stakes environments.
  • Build reusable deployment patterns and playbooks, capturing integration, testing, observability, and operational learnings so future deployments become more repeatable and supportable.
  • Travel as needed (30–75%, depending on the customer) to integrate, test, and validate systems in real-world environments.

Desired Qualifications

  • Strong problem-solving skills and the ability to operate effectively in ambiguous, fast-moving environments.
  • Comfort working directly with customers and communicating technical concepts clearly.
  • Comfort spending significant time embedded with customer teams when deployment needs require it.
  • Senior-level expectations: 5+ years of experience; write clean, idiomatic, well-tested code or output, follow best practices, drive debugging of the team's hardest issues, ensure AI-assisted work is correct, modular, and fully tested, design and implement changes to single systems, collaborate on larger designs, drive architecture reviews for multi-developer projects, work with Product to scope and de-risk work, provide reliable estimates for medium-sized projects with clear risk communication, mentor and onboard teammates, and contribute to interviews and candidate experience.
  • Staff-level expectations: 7+ years of experience; define and enforce the team's testing strategy, standards, and quality bar, ensure AI-generated output is tightly integrated into existing paradigms and robustly tested, design cross-cutting changes across the stack, provide architectural guidance across the team, own design documents for major multi-service or multi-surface projects, own technical scoping and execution strategy for complex multi-sprint initiatives, audit requirements for technical risk and hidden dependencies, serve as the primary technical gatekeeper for the team's codebase, review high-impact work, lead technical grooming, design spikes, and requests for comments, and coordinate across pods when changes cross domain boundaries.
  • Principal-level expectations: 10+ years of experience; set the quality and correctness bar across the department, improve automated systems and practices that ensure department-wide quality, provide architectural guidance across the department and invent paradigms for translation, optimization, and deployment across target environments, contribute consistently to the company's technical roadmap, estimate large cross-team initiatives, scope work pragmatically toward valuable outcomes, drive company-wide architectural reviews and proposals, mentor mid-level and senior staff at scale, and influence technical outcomes across departments.

About the Company

Code Metal

Optimizes research code for edge deployment

CodeMetal.ai provides a SaaS platform that turns research code into optimized, edge-ready low-level code. It serves academia, defense, and tech sectors in AI and machine learning. Users upload code written in Python, Julia, or MATLAB, pick target deployment chipsets, and the platform automatically optimizes the code and adapts it to chosen runtimes, iteratively improving performance. This approach differentiates CodeMetal.ai by offering multi-language support, chipset-aware optimization, and runtime adaptation within a cloud-based service, enabling users to deploy efficient code on edge devices without manual low-level tuning. The company's goal is to help clients run more efficient AI/ML workloads on edge hardware by converting high-level research code into fast, platform-optimized implementations via subscriptions and usage-based pricing.

Company size
51-200
Company stage
Series B
Total funding
$177.7M
Headquarters
Boston, MA
Founded
2023

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