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LLM Trainer - Cuda/C++ to Python migration

Typical $25–60/hr Worldwide Remote · worldwide coding Contract / freelance
Pay rate · Typical $25–60/hr
Typical hourly range for this type of role — the exact rate is confirmed by the hiring company.

Overview

Optimize and migrate CUDA code to Python for AI model training.

About the hiring company

  • The hiring company is one of the world’s fastest-growing AI companies accelerating the advancement and deployment of powerful AI systems.
  • The hiring company helps customers in two ways: Working with the world’s leading AI labs to advance frontier model capabilities in thinking, reasoning, coding, agentic behavior, multimodality, multilinguality, STEM and frontier knowledge; and leveraging that work to build real-world AI systems that solve mission-critical priorities for companies.

Role Overview

  • We are looking for experienced CUDA Developers to work on cutting-edge AI and machine learning projects. In this role, you will contribute to improving large language model (LLM) capabilities by solving complex coding problems, optimizing GPU-based workloads, reviewing model-generated code, and helping train AI systems to produce high-quality CUDA and parallel computing solutions.
  • The ideal candidate should have strong expertise in CUDA, GPU programming, parallel computing, performance optimization, and Python-based machine learning ecosystems.

What does day-to-day look like

  • Solve advanced CUDA and parallel computing problems involving GPU acceleration and performance optimization.
  • Review, evaluate, and improve AI-generated CUDA/C++/Python code.
  • Analyze GPU kernel performance and optimize algorithms for throughput, latency, and memory efficiency.
  • Work with CUDA libraries and frameworks such as Thrust, cuBLAS, and cuDNN.
  • Develop high-quality prompts, solutions, explanations, and evaluations to improve AI model reasoning and coding performance.
  • Debug and resolve issues related to CUDA kernels, memory management, synchronization, and resource utilization.
  • Collaborate with cross-functional teams working on AI model training and evaluation.
  • Stay updated with the latest developments in CUDA, GPU architectures, and parallel computing best practices.

Requirements

  • Bachelor’s degree in Computer Science, Computer Engineering, or a related technical field.
  • 5+ years of professional software development experience with strong focus on

CUDA

  • development.
  • Strong proficiency in

C/C++.

Strong hands-on experience with

Python

  • , especially in scientific computing using PyTorch and NumPy.
  • Experience working with CUDA version 12.3 or above.
  • Strong understanding of GPU programming concepts, parallel computing, and performance optimization.
  • Experience optimizing code for efficient resource utilization and high-performance execution.
  • Familiarity with CUDA frameworks and libraries such as Thrust, cuBLAS, and cuDNN.
  • Ability to solve complex technical problems independently.
  • Strong written and verbal communication skills.
  • Prior experience contributing to AI/ML systems or LLM-related projects is a plus.

Perks of Freelancing With the hiring company

  • Work in a fully remote environment.
  • Opportunity to work on cutting-edge AI projects with leading LLM companies.

Offer Details

Commitments Required

At least 4 hours per day and minimum 20 hours per week with overlap of 4 hours with PST. (We have 3 options of time commitment: 20 hrs/week, 30 hrs/week or 40 hrs/week)

Engagement type

Contractor assignment (no medical/paid leave)

Duration of contract

: 3 months; [expected start date is next week]

Evaluation Process (approximately 60 mins)

One round of Technical interviews

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