Stealth AI Chip Startup
LLM algorithm/software engineer
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Company Description
Stealth AI Chip Startup is focused on building next-generation AI hardware to power large language models and advanced agentic applications. The team is dedicated to designing high-performance chips that significantly accelerate training and inference workloads at scale. By tightly integrating hardware and software, the company aims to unlock new capabilities in AI-driven products and services. Joining the startup offers the opportunity to work on cutting-edge systems, influence core architectural decisions, and shape the future of AI computation.
Role Description
The LLM Algorithm/Software Engineer will design, implement, and optimize software and algorithms that run on our next-generation AI chips, with a focus on large language models and agentic workloads. Day-to-day responsibilities include:
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- Building and maintaining back-end systems
- Writing production-quality code
- Profiling and optimizing performance
- Collaborating with hardware engineers to co-design algorithms and architectures
- Experimenting with new model architectures
- Integrating LLM frameworks
- Contributing to tooling and infrastructure for model deployment and evaluation
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This is a full-time, on-site role based in Edinburgh, working closely with a small, multidisciplinary team in a fast-paced startup environment.
Qualifications
- Strong foundation in Computer Science, including algorithms, data structures, and systems concepts.
- Proficiency in Software Development and Programming, with experience building reliable, scalable services.
- Hands-on experience in Back-End Web Development, including APIs, microservices, and performance optimization.
- Solid understanding of Object-Oriented Programming (OOP) principles and clean code practices.
- Experience with LLMs or modern deep learning frameworks (e.g., PyTorch, TensorFlow, JAX) and related tooling.
- Comfort working close to hardware (e.g., GPUs, AI accelerators), including profiling, low-level optimization, or compiler-related work.
- Bachelor’s or advanced degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
- Ability to collaborate in an on-site team setting, communicate clearly, and take ownership of complex technical problems.
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