2

Remote High Performance Computing Engineer Jobs in Colorado

Sr. Storage Software Developer

Longmont, CO · On-site +1

$54 - $71.25/hr

... high-performance computing market. We are seeking a highly experienced Senior Storage Software ... However, we are open to remote candidates who meet the qualifications and can work effectively from ...

Sr. Storage Software Developer

Niwot, CO · On-site +1

$54 - $71.25/hr

... high-performance computing market. We are seeking a highly experienced Senior Storage Software ... However, we are open to remote candidates who meet the qualifications and can work effectively from ...

VDURA is redefining high-performance data infrastructure for AI, HPC, and data-intensive workloads ... However, we are open to remote candidates who meet the qualifications and can work effectively from ...

VDURA is redefining high-performance data infrastructure for AI, HPC, and data-intensive workloads ... However, we are open to remote candidates who meet the qualifications and can work effectively from ...

Geospatial Platform Lead

Boulder, CO · On-site +1

$100K - $135K/yr

Standards & reliability: set engineering standards, including Infrastructure-as-Code on AWS; keep ... Distributed or large-scale processing (e.g., Dask, cloud batch) and high-performance computing.

Key Account Manager

Denver, CO · On-site +1

$100K - $150K/yr

Remote Compensation: $100,000 - $150,000 Base About this position Advantech is seeking a driven and ... high-performance computing platforms. We cooperate closely with our partners to help provide ...

next page

Showing results 1-20

Remote High Performance Computing Engineer information

What is the difference between Remote High Performance Computing Engineer vs Remote Data Scientist?

AspectRemote High Performance Computing EngineerRemote Data Scientist
Required CredentialsBachelor's or Master's in Computer Science, Engineering, or related field; experience with HPC systemsBachelor's or Master's in Data Science, Statistics, or related field; proficiency in programming and analytics
Work EnvironmentDesigning, optimizing, and maintaining HPC systems remotely for scientific or engineering tasksAnalyzing large datasets, building models, and generating insights remotely for various industries
Employer & Industry UsageTech companies, research institutions, engineering firms using HPC clustersTech, finance, healthcare, and research organizations leveraging data analytics

While both roles often require strong programming skills and familiarity with cloud or remote systems, the HPC Engineer focuses on maintaining and optimizing high-performance computing infrastructure, whereas the Data Scientist emphasizes data analysis and modeling. Their work environments overlap in remote settings, but their core responsibilities differ significantly.

Are remote high performance computing engineers in demand?

Remote high performance computing (HPC) engineers are in high demand due to the increasing need for processing large datasets and complex simulations across industries like research, finance, and technology. Skills in parallel programming, cluster management, and knowledge of tools such as MPI and CUDA enhance employability in this growing field.

How much do remote high performance computing engineers make in the US?

Remote high performance computing (HPC) engineers in the US typically earn between $80,000 and $150,000 annually, depending on experience, education, and specific industry. Senior roles or those requiring specialized skills in parallel processing, cluster management, or GPU computing may offer higher salaries, especially with certifications or advanced degrees.
What are the most commonly searched types of High Performance Computing Engineer jobs in Colorado? The most popular types of High Performance Computing Engineer jobs in Colorado are:
What cities in Colorado are hiring for Remote High Performance Computing Engineer jobs? Cities in Colorado with the most Remote High Performance Computing Engineer job openings:

Staff Engineer, Inference Optimizations

DigitalOcean

Denver, CO • Remote

$191K - $239K/yr

Full-time

Posted 18 days ago


Job description

DigitalOcean is seeking a Senior Engineer 2 to play a key technical role in our AI Inference Optimization team. DigitalOcean aims to be the Inference Cloud of choice for digitally native companies and you will help ensure we can offer the industry-leading performance for our inference services. You will be responsible for the architectural decisions that maximize throughput and minimize latency for the world's most advanced large models. As an IC leader, you will act as a force multiplier for the engineering organization, solving the most complex bottlenecks in memory bandwidth and compute utilization while guiding the technical roadmap for our high-performance inference fleet.

What You'll Do:
  • Performance Architecture: Lead the technical strategy for benchmarking and performance optimizations at the inference engine and GPU kernel layers, ensuring our infrastructure extracts maximum value from every TFLOP.
  • Deep-Dive Optimization: Engineer solutions for complex performance issues, including attention layer optimizations, memory and precision management, and advanced parallelization across multi-node GPU clusters. 
  • Technological Innovation: Proactively implement cutting-edge optimization techniques to keep DigitalOcean at the forefront of the Gen AI landscape. Some examples of projects you may work on:
    • Improving batch size performance using AMD's AITER library for AMD MI355X - identify and tune AITER's CK (composable kernel) or ASK (assembly) to optimize FP8 / BF16 
    • Identify kernel fusion opportunities for GLM-5 kernels for different layers of the Transformer block (FlashAttention, RMS Norm)
    • Tune expert gateway router kernels for MoE models like Qwen3-235B, DeepSeek V3, GLM-5 etc
  • Hardware & Ecosystem Mastery: Act as the subject matter expert on modern GPU families (NVIDIA/AMD) and their software stacks (CUDA, ROCm, TensorRT, OpenAI Triton), advising on hardware procurement and software integration.
  • Precision Optimization: Develop and deploy state-of-the-art quantization techniques (FP8, INT8, and experimental FP4) to double throughput without losing accuracy.
  • Technical Mentorship: Lead by example through high-quality code and design reviews, elevating the technical bar for the team without the administrative overhead of direct management.
  • Strategic Collaboration: Partner with Product Management and TPMs to translate "theoretical hardware limits" into "shippable product features," ensuring our platform is both powerful and developer-friendly.
  • Community Leadership: Maintain a strong presence in the GPU infrastructure and model performance optimization communities, contributing to and integrating the best of open-source AI.
What You'll Bring to DigitalOcean:
  • Technical Depth: 5+ years of experience in high-performance computing or AI infrastructure, with a proven track record of solving compute utilization and memory bandwidth bottlenecks.
  • Gen AI Literacy: Deep familiarity with the Gen AI (LLM, VLM, LMM) landscape, including the specific quirks and architectural requirements of major model families.
  • Optimization Expert: Hands-on experience with attention-layer optimizations and parallelization strategies across distributed GPU environments.
  • Hardware Fluency: Comprehensive understanding of NVIDIA and AMD GPU architectures and their respective software ecosystems (CUDA, ROCm, etc.).
  • Open Source Mastery: Extensive experience integrating, building with, and contributing to open-source software projects.
  • Systems Design: Excellent system design skills, particularly related to low-level GPU programming - optimization, memory access patterns, and parallel execution.
  • Leadership through Influence: Experience acting as a technical lead, driving design and delivery through cross-functional alignment and expert-level delegation.
  • Low-Level Mastery: Deep understanding of GPU architectures (SMs, Warp scheduling, Tensor Cores).
  • The Toolkit: Expert-level Triton or CUDA. If you've contributed to the Triton compiler or wrote custom CUDA kernels for a major LLM, we want you.
Compensation Range: 
  • $191,200 - $239,000

*This is a remote role

JR: 2026-7625

#LI-Remote