CUDA Developer for AI Model Training

Role Overview:

Join a dynamic team focused on advancing AI and machine learning capabilities as a CUDA Developer. In this role, you will enhance large language model (LLM) functionalities by tackling complex coding challenges, optimizing GPU workloads, and refining AI-generated code. Your expertise will be pivotal in developing high-quality CUDA and parallel computing solutions that drive real-world applications.

Key Responsibilities:

• 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.

Qualifications:

• Bachelor’s degree in Computer Science, Computer Engineering, or a related technical field.
• 5+ years of professional software development experience with a strong focus on CUDA development.
• Strong proficiency in C/C++.
• Hands-on experience with Python, particularly 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.

Work Terms:

• Commitments Required: At least 4 hours per day and a minimum of 20 hours per week with 4 hours of overlap with PST. (Options for 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

Compensation:

Compensation details will be discussed during the interview process.

Eligibility:

This position is fully remote and open to candidates with the required qualifications.