Senior AI Compiler Engineer – Applied Research

🔥 1 minute ago

🏄 California, Texas, +1 more states – Remote

🏄 California – Remote 🤠 Texas – Remote ☕ Washington – Remote

💵 $152k - $241.5k / year

⏰ Full Time

🟠 Senior

🤖 Artificial Intelligence

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NVIDIA

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1993

🤖 Artificial Intelligence

🎮 Gaming

Artificial Intelligence • Gaming • Automotive

NVIDIA is a leading technology company specializing in accelerated computing and artificial intelligence. NVIDIA pioneers advancements in graphical processing units (GPUs), cloud computing, data centers, and virtual reality, with a focus on gaming, automotive, healthcare, and robotics industries. The company's innovations, such as NVIDIA Omniverse, transform traditional digital processes by enabling high-fidelity simulations and rendering tasks. Their applications span various industries, from autonomous vehicles using NVIDIA DRIVE to healthcare solutions with NVIDIA Clara, and AI-driven analytics and workflows.

📋 Description

• Help trailblaze company efforts in applying AI within conventional compilation pipelines • Design and implement AI-based technology addressing core problems of low-level GPU programming • Build training pipelines for supervised fine-tuning and reinforcement learning (RL/RLHF-style or policy optimization variants) • Define model inputs/outputs over compiler low level compiler representations • Develop evaluation frameworks to measure code quality, runtime, compile-time overhead, and correctness • Intelligent (domain` task based) prompt engineering • Collaborate with compiler engineers to integrate learned policies into production toolchains • Prototype and iterate on model architectures, prompts, and fine-tuning strategies for scheduling and allocation tasks • Create datasets from compiler traces, optimization passes, and target-specific performance signals • Apply RL techniques to optimize for downstream objectives (performance, spill reduction, instruction-level parallelism, etc.) and run rigorous experiments, ablations, and benchmarking across workloads and hardware targets

🎯 Requirements

• M.S./PhD degree in Computer Engineering, Computer Science related technical field (or equivalent experience) • 5+ years of experience building AI/ML systems • Strong software engineering skills in Python and at least one systems language (C++ preferred) • Hands-on experience training/fine-tuning large models (Transformers, PEFT/LoRA, distributed training) • Solid understanding of machine learning fundamentals and experimentation best practices • Experience with reinforcement learning (e.g., policy gradients, actor-critic, offline RL, bandit-style optimization) • Knowledge of prompt-engineering techniques • Ability to work across research and engineering, from prototype to production

🏖️ Benefits

• equity • benefits