Posted today
Secret
Mid Level Career (5+ yrs experience)
$80,000 - $150,000
Occasional travel
IT - Software
Colorado Springs, CO (On/Off-Site)
CUDA Developer – 6 Open Positions
Location: Remote or On‑Site (Flexible)
Employment Type: Full‑Time
About the Role
DARC is hiring six skilled CUDA Developers to help build the next generation of GPU‑accelerated applications. In this role, you will design, optimize, and implement high‑performance software that leverages NVIDIA’s CUDA platform to deliver massive computational speedups for advanced AI, scientific computing, real‑time graphics, and other performance‑critical workloads.
If you are passionate about parallel programming, cutting-edge hardware, and pushing the limits of GPU performance, this is the team you’ll want to join.
What You’ll Do
Develop and optimize CUDA kernels for high‑performance, parallel execution on NVIDIA GPUs
Accelerate compute‑intensive applications in areas such as AI/ML, simulation, scientific computing, and graphics
Work closely with engineering teams to redesign algorithms for GPU parallelization
Perform GPU profiling and optimization (memory coalescing, shared memory tuning, occupancy optimization)
Integrate CUDA workloads into larger C/C++ and/or Python codebases
Collaborate with cross‑functional teams to deliver scalable, GPU‑accelerated solutions
Troubleshoot performance bottlenecks and propose enhancements
What We’re Looking For
Strong experience with CUDA programming and GPU‑accelerated development
Proficiency in C/C++ (Python experience is a plus)
Solid understanding of GPU architecture (threads, blocks, warps, shared vs. global memory)
Experience optimizing algorithms for parallel execution
Familiarity with tools such as:
NVIDIA Nsight
cuBLAS, cuDNN, cuFFT, Thrust
Background in one or more of the following:
Machine learning or deep learning
Scientific/HPC workloads
Computer vision or real‑time graphics pipelines
Numerical simulation or physics engines
Bachelor’s or Master’s in Computer Science, Engineering, or equivalent experience
Nice-to-Have Skills
Experience with TensorRT, PyTorch, or TensorFlow internals
Knowledge of PTX or low-level GPU optimization
Distributed computing experience (MPI, NCCL, multi‑GPU systems)
Familiarity with cloud GPU environments (AWS, Azure, GCP)
**Eligibility requirements apply to some benefits and may depend on your job classification and length of employment. Benefits are subject to change and may be subject to specific elections, plan, or program terms. If eligible, the benefits available for this temporary role may include the following:
Medical, dental & vision
Critical Illness, Accident, and Hospital
401(k) Retirement Plan – Pre-tax and Roth post-tax contributions available
Life Insurance (Voluntary Life & AD&D for the employee and dependents)
Short and long-term disability
Health Spending Account (HSA)
Transportation benefits
Employee Assistance Program
Time Off/Leave (PTO, Vacation or Sick Leave)
Location: Remote or On‑Site (Flexible)
Employment Type: Full‑Time
About the Role
DARC is hiring six skilled CUDA Developers to help build the next generation of GPU‑accelerated applications. In this role, you will design, optimize, and implement high‑performance software that leverages NVIDIA’s CUDA platform to deliver massive computational speedups for advanced AI, scientific computing, real‑time graphics, and other performance‑critical workloads.
If you are passionate about parallel programming, cutting-edge hardware, and pushing the limits of GPU performance, this is the team you’ll want to join.
What You’ll Do
Develop and optimize CUDA kernels for high‑performance, parallel execution on NVIDIA GPUs
Accelerate compute‑intensive applications in areas such as AI/ML, simulation, scientific computing, and graphics
Work closely with engineering teams to redesign algorithms for GPU parallelization
Perform GPU profiling and optimization (memory coalescing, shared memory tuning, occupancy optimization)
Integrate CUDA workloads into larger C/C++ and/or Python codebases
Collaborate with cross‑functional teams to deliver scalable, GPU‑accelerated solutions
Troubleshoot performance bottlenecks and propose enhancements
What We’re Looking For
Strong experience with CUDA programming and GPU‑accelerated development
Proficiency in C/C++ (Python experience is a plus)
Solid understanding of GPU architecture (threads, blocks, warps, shared vs. global memory)
Experience optimizing algorithms for parallel execution
Familiarity with tools such as:
NVIDIA Nsight
cuBLAS, cuDNN, cuFFT, Thrust
Background in one or more of the following:
Machine learning or deep learning
Scientific/HPC workloads
Computer vision or real‑time graphics pipelines
Numerical simulation or physics engines
Bachelor’s or Master’s in Computer Science, Engineering, or equivalent experience
Nice-to-Have Skills
Experience with TensorRT, PyTorch, or TensorFlow internals
Knowledge of PTX or low-level GPU optimization
Distributed computing experience (MPI, NCCL, multi‑GPU systems)
Familiarity with cloud GPU environments (AWS, Azure, GCP)
**Eligibility requirements apply to some benefits and may depend on your job classification and length of employment. Benefits are subject to change and may be subject to specific elections, plan, or program terms. If eligible, the benefits available for this temporary role may include the following:
Medical, dental & vision
Critical Illness, Accident, and Hospital
401(k) Retirement Plan – Pre-tax and Roth post-tax contributions available
Life Insurance (Voluntary Life & AD&D for the employee and dependents)
Short and long-term disability
Health Spending Account (HSA)
Transportation benefits
Employee Assistance Program
Time Off/Leave (PTO, Vacation or Sick Leave)
group id: 10105424
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