System Software Engineer - AI

Reposted 21 Hours Ago
Hiring Remotely in USA
Remote
140K-200K Annually
Mid level
Artificial Intelligence • Hardware • Semiconductor
Stronger Network. Faster Inference.
The Role
As a System Software Engineer, you will design communication primitives for AI models, optimize performance for training workloads, and benchmark performance on clusters.
Summary Generated by Built In

System Software Engineer - AI

About us:

We are a stealth-mode startup building foundational technology to address performance, scalability, and resiliency challenges in large-scale AI data center clusters. We are backed by top-tier VC firms and notable angel investors.

The company is led by experienced builders and operators who have founded companies, taken them to scale, and exited successfully. We work with a strong sense of unity and shared responsibility, and we expect trust, integrity, and respect in how we collaborate and make decisions. We hold ourselves accountable to one another and to the quality of the work we deliver.

Headquartered in Silicon Valley, we operate across a mix of remote and on-site locations in the U.S. and Canada. We aim to create an environment where people are treated fairly, supported in their growth, and are empowered to do meaningful work alongside others who take the craft seriously.

We are looking for:

We are looking for a talented System Software Engineer to help us redefine the infrastructure layer of AI. In this role, you will bridge the gap between high-level AI frameworks and low-level system software. You will be responsible for designing and implementing the communication and execution primitives that allow large-scale AI models to run efficiently across thousands of GPUs. We are looking for a "builder" who thrives in the early stages of a product’s lifecycle and is passionate about solving the "hard" systems problems of the generative AI era.

Key Responsibilities:

  • Collaborate across the stack to influence the design of our foundational technology, ensuring it meets the needs of next-generation AI models.

  • Identify and resolve performance bottlenecks in distributed training and inference workloads through deep-dive analysis of the software-hardware interface.

  • Conduct rigorous performance benchmarking and characterization on multi-node clusters.

Required Skills and Qualifications:

  • Strong proficiency in C++ and Python, with a deep understanding of systems programming fundamentals (memory management, concurrency, OS internals).

  • Proficient in a Linux development environment.

Desired Skills:

  • Experience with GPU programming (CUDA) and performance optimization for parallel architectures.

  • Familiarity with distributed AI frameworks (PyTorch, JAX, or DeepSpeed) and/or inference engines (vLLM, SGLang, Dynamo/TRT-LLM).

  • Hands-on experience with large-scale cluster orchestration and telemetry tools.

Education:

  • Bachelor's or Master's degree in Computer Engineering, Computer Science, or a related field.

Compensation:

Target base salary for this role is $140,000 - $200,000 per year + meaningful equity + benefits + 401k. Our salary ranges are determined by role, level, experience, and location.

We are an equal opportunity employer. We value a range of perspectives and experiences and make employment decisions based on merit and business needs. We do not discriminate on the basis of legally protected characteristics.

Agency Note:

We do not accept resumes from agencies or search firms. Please do not forward candidate profiles through our careers page, email, LinkedIn messages, or directly to company employees. Any resumes submitted will be deemed the property of the company, and no fees will be paid in the event the candidate is hired.

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The Company
40 Employees
Year Founded: 2025

What We Do

We are a mixture of software, system, and silicon experts using AI every day to deliver the world's most capable and responsive intelligence.

Why Work With Us

We are a mixture of software, system, and silicon experts using AI every day to deliver the world's most capable and responsive intelligence. We start from the workload. Scaling inference is less about brute force and more about how compute is distributed and memory is interc

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