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Delos Data Inc

System Software Engineer - AI

Palo Alto, California, United States

Location
Palo Alto, California, United States
Work
Hybrid
Employment
Full-time
Level
Not stated
Function
Engineering
Pay
$140K – $220K a year (read from the ad)
Posted
3 months ago

About the role

System Software Engineer - AI

About us

We are a 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.

Some Recent Press

https://www.eetimes.com/startup-boosts-scale-up-to-1000-gpus-in-a-single-domain/

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

  • 5+ Years experience.
  • 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.
  • Familiarity with networking protocols and concepts.

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.
  • Experience deploying systems to production and managing the release lifecycle.

Education

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

Location

This is a hybrid role based in Palo Alto or Charlottesville, VA.

Compensation

Target base salary for this role is $140,000 - $220,000 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.

#LI-EW1

Source

Posted by Delos Data Inc on their own hiring page, jobs.ashbyhq.com. OptiTalent shows it as published, read 07 Nov 2026 03:00 UTC; the original is the reference.

View the original ad ↗

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