Full-Time
Senior Principal Software Engineer
Modeling & Simulation
Code Metal
11-50 employees
Transforms research code into optimized low-level code
No salary listed
Senior, Expert
Boston, MA, USA
Hybrid
Flexible hybrid work arrangement; Relocation assistance for qualifying employees.
US Top Secret Clearance Required
- Master’s degree (or equivalent) in applied math, scientific computing, physics, or a related field.
- Proven expertise in multi-threaded C++ for high-performance applications.
- Hands-on experience with large-scale, physics-based simulations.
- Active Secret clearance (or higher).
- Design & implement a scalable, interactive physics simulation that runs seamlessly in cloud and on-prem clusters.
- Own the core codebase in modern C++ from multi-threaded performance tuning to continuous integration.
- Collaborate with product & AI teams to embed verified, AI-generated algorithms directly into a developer SDK for extending the platform.
- Prototype quickly, iterate faster: deliver usable capability to government end-users in weeks, not months.
- Set the engineering bar—write clean code, document rigorously, and mentor teammates through code reviews and pair programming.
- PhD (or equivalent depth) in applied math, scientific computing, physics, or similar.
- GPU compute chops—OpenCL, CUDA, etc....
- Data oriented framework design experience like ECS.
- Prior work running physics simulations in distributed cloud environments.
- TS/SCI clearance.
CodeMetal.ai transforms research code into optimized low-level code suitable for edge deployment. Users can upload their code written in Python, Julia, or MATLAB to the company's SaaS platform, where they can select specific chipsets for deployment. The platform automates the optimization process, enhancing code efficiency by adapting to the chosen runtimes and iteratively improving performance. Unlike competitors, CodeMetal.ai focuses specifically on the needs of clients in academia, defense, and tech industries, providing tailored solutions for code optimization. The company's goal is to streamline the deployment of machine learning and AI applications by making research code more efficient and ready for real-world use.
Company Size
11-50
Company Stage
Seed
Total Funding
$16.2M
Headquarters
Boston, Massachusetts
Founded
2023
Simplify's Take
What believers are saying
- Code Metal raised $16.5M, indicating strong investor confidence and growth potential.
- The rise of edge AI in retail and manufacturing expands Code Metal's market opportunities.
- Increasing demand for low-level code optimization aligns with Code Metal's core competencies.
What critics are saying
- OpenAI's 'Deep Research' tool may reduce demand for Code Metal's services.
- Rapid advancements by competitors could outpace Code Metal's current offerings.
- Potential security vulnerabilities in automated processes could impact client trust.
What makes Code Metal unique
- Code Metal specializes in transforming research code into optimized, edge-ready low-level code.
- The platform supports Python, Julia, and MATLAB, catering to diverse programming needs.
- Code Metal automates code optimization for specific chipsets, enhancing runtime efficiency.
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Benefits
Health Insurance
401(k) Company Match
401(k) Retirement Plan
Unlimited Paid Time Off
Hybrid Work Options
Relocation Assistance
Growth & Insights and Company News
6 month growth
↑ 3%1 year growth
↓ -9%2 year growth
↓ -9%OpenAI’s new “Deep Research” tool is poised to transform how businesses gather intelligence and shape their corporate strategy, according to experts. But it does come with some key caveats. Deep Research is an artificial intelligence (AI)-driven research assistant that can search the web for in-depth information about a topic and then generate a detailed report at the level of a research analyst in “tens of minutes,” according to OpenAI, which publicly demonstrated the tool on Sunday (Feb. 2). “It is particularly effective at finding niche, non-intuitive information that would require browsing numerous websites,” OpenAI said in a blog post. “Deep Research frees up valuable time by allowing you to offload and expedite complex, time-intensive web research with just one query.”
Ayon Basumallik joins Code Metal as SVP of Engineering and Product.
A pair of AI researchers from MIT Lincoln Laboratory have launched a startup called Code Metal, which focuses on translating AI software to run on various hardware like drones and robots. The company raised $13 million in seed capital led by Shield Capital and previously secured $3.5 million in pre-seed funding from J2 Ventures and Fulcrum Venture Group. Code Metal's technology uses large language models to automate software translation, significantly reducing development time.
Code Metal, a leading company in AI-powered development workflows for the edge, has raised $13 million in a seed funding, led by Shield Capital, and a prior $3.45 million pre-seed round, led by J2 Ventures, with support from Fulcrum Venture Group, Underdog Labs, and others.
AI’s integration with edge computing is accelerating as tech firms vie to offer faster, localized data processing — a shift that could reshape retail, supply chains and customer experiences.Edge computing processes data near where it’s created instead of in distant cloud servers. Companies like Code Metal, which recently secured $16.45 million in funding, are creating AI-driven workflows hoping to reduce product development times. It’s part of a growing shift to edge computing for AI, which could significantly impact commerce.“AI and Edge Computing have created some fascinating use cases for businesses with brick-and-mortar operations that need to be monitored,” Aaron Allsbrook, CTO of edge computing company ClearBlade, told PYMNTS. “For example, intelligent video analytics can flag onsite issues like low stock, customer dwell times or occupancy rates.”Experts say the convergence of AI and edge computing could reshape various facets of commerce. Retailers might leverage AI-enhanced edge devices for real-time inventory management and personalized in-store experiences. Manufacturing plants could use AI-powered edge systems to optimize production lines and predict maintenance needs more accurately