C

Code Metal

Optimizes research code for edge deployment

Staff Python Engineer - Modeling & Simulation

Backend EngineeringConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • Professional experience developing collaborative, enterprise-level software in Python and delivering products to a large customer base.
  • Experience gathering stakeholder requirements and translating them into software designs.
  • Experience building and delivering robust software using software development lifecycle practices, including code review, testing, continuous integration, release management, and build systems.
  • Familiarity with machine learning tools and frameworks.
  • Expertise building scalable APIs using REST, GraphQL, and gRPC.
  • Hands-on experience with Docker and containerized application development.
  • Eligibility to obtain and maintain an active U.S. Top Secret security clearance.
  • At least 7 years of experience for the Staff level.

Responsibilities

  • Design and implement backend services and APIs that orchestrate mission- and campaign-level simulation runs, collect outputs, and expose results to analysts and government stakeholders.
  • Build scenario-generation, operational and mission-planning workflows, and services for Monte Carlo-based sensitivity analysis for the wargaming and decision-support platform.
  • Build distributed, cloud-scale infrastructure to scale simulations across developer workstations, on-premises infrastructure, and cloud compute while preserving reproducibility and model provenance.
  • Build data ingestion, normalization, and analysis pipelines that turn raw simulation output into decision-ready insight for defense users.
  • Build scalable APIs and containerized services connecting the Python tooling layer to the core simulation runtime and downstream analysis tools.
  • Gather requirements from government stakeholders, domain experts, and analysts, and distill them into clear software designs.
  • Use software development lifecycle practices throughout the work, including code review, testing, continuous integration, release management, and build systems.
  • Define and enforce the team's testing strategy, standards, and quality bar, and ensure AI-generated output is integrated into existing paradigms and robustly tested.
  • Design cross-cutting changes across the stack, provide architectural guidance across the team, and own design documents for major multi-service or multi-surface projects.
  • Own technical scoping and execution strategy for complex, multi-sprint initiatives, and audit requirements for technical risks and hidden dependencies before development begins.
  • Serve as the primary technical gatekeeper for the team's codebase, review high-impact work, lead technical grooming, design spikes, and RFCs, and coordinate across pods when changes cross domain boundaries.

Desired Qualifications

  • Familiarity with agentic AI frameworks and solutions.
  • Familiarity with code analysis and static analysis.
  • Experience working with cloud-based distributed systems, including AWS, GCP, or Azure.
  • An active U.S. security clearance, such as Secret, Top Secret, or SCI/SAP.
  • Direct experience developing AFSIM plugins, framework extensions, event infrastructure, or custom platform types.
  • Familiarity with HLA, DIS, OneSAF, JSAF, NGTS, STK, or other constructive and distributed simulation environments.
  • Experience supporting Air Force, Space Force, joint, or broader DoD acquisition and mission-analysis programs.
  • Experience developing models for sensors, weapons, electronic warfare, jamming, communications, logistics, or command and control.

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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