CUDA Developer for AI Model Training

Role Overview:

Join a dynamic team focused on advancing large language model (LLM) capabilities through innovative AI and machine learning projects. In this role, you will leverage your expertise in CUDA and GPU programming to tackle complex coding challenges, optimize GPU-based workloads, and enhance AI systems'' performance. Your contributions will be vital in producing high-quality CUDA and parallel computing solutions.

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, 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.

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 include 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:

Competitive compensation based on experience.

Eligibility:

This position is fully remote, allowing you to work from anywhere.

Perks of Freelancing:

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

Evaluation Process:

One round of technical interviews, approximately 60 minutes in duration.