Senior Software Engineer, CUDA Deep Learning Systems

About This Opportunity

Our talent team is representing a confidential technology organization at the forefront of AI systems innovation. We are seeking a Senior Software Engineer to join a research-oriented team working at the intersection of GPU computing and deep learning systems. This role focuses on pioneering work that bridges advanced AI architectures with low-level hardware optimization, pushing the boundaries of performance on modern accelerator platforms.

You will explore next-generation optimizations spanning from single-node systems to massive distributed computing clusters, developing custom kernels and runtime systems for emerging neural network workloads. This is an opportunity to work on uncharted problems in model optimization and cluster-scale AI design.

Responsibilities

• Research and prototype novel systems optimizations for advanced deep learning models, bridging high-level frameworks and low-level CUDA through modeling, simulation, and hardware prototyping
• Architect and optimize distributed computing systems that scale from single nodes to cluster-scale supercomputing environments
• Design, implement, and optimize custom high-performance CUDA kernels for emerging neural network architectures
• Analyze complex hardware-software interactions to identify and resolve performance bottlenecks in training and inference pipelines
• Collaborate with AI researchers, hardware and software architects, kernel developers, and compiler experts to co-design systems that improve compute utilization, memory bandwidth, and network communication efficiency
• Develop exploratory profiling tools and runtime systems to accelerate new paradigms in deep learning
• Write clean, maintainable code ensuring prototypes can transition into open-source releases, framework integrations, or commercial products

What We're Looking For

Required qualifications:

• BS, MS, or PhD in Computer Science, Computer Engineering, Electrical Engineering, or related field (or equivalent experience)
• 8+ years of relevant industry or academic experience after degree completion
• Strong proficiency in C++ and Python programming
• Solid background in deep learning fundamentals with focus on transformer architectures
• Strong understanding of distributed computing principles, multi-node scaling, and cluster-scale performance challenges
• Proven experience in systems programming, computer architecture, and low-level performance optimization
• Familiarity with GPU accelerator architectures and hands-on CUDA programming, kernel optimization, and workload profiling experience
• Experience profiling and optimizing generative AI models, including large language models
• Research background in machine learning systems or adjacent fields
• Track record of initiative and willingness to deep-dive on problems across the stack

Preferred qualifications:

• Deep expertise in performance internals and execution graphs of major deep learning frameworks (PyTorch, JAX, TensorRT, vLLM, sgLang)
• Hands-on experience with communication libraries (NCCL, MPI, UCX) and distributed ML techniques (pipeline, tensor, expert parallelism)
• Knowledge of numerical methods and low-precision arithmetic (FP8, INT8, etc.) and their impact on accuracy and performance
• Background in deep learning compilers and ML systems, including graph-level tools (Triton, XLA, torch.compile)
• Experience designing and implementing agentic AI systems for complex infrastructure problems

How We Work With You

Candidates apply directly through Get A Job.ai. Our recruiting team conducts an initial screen to understand your background and ensure alignment with the role requirements. We then submit qualified candidates to our client for consideration. Please do not attempt to contact the client directly, as all communications are managed through our team to ensure a professional and coordinated process.

Pay

Compensation details will be discussed during the screening process based on experience level and qualifications. You will also be eligible for equity and benefits through the client organization.

Equal Employment Opportunity: Get A Job.ai is committed to inclusive recruiting practices. We welcome applications from candidates of all backgrounds and do not discriminate on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by law.