4 days ago
Base Salary
$224k - $357k/yr
Responsibilities
- Drive AI solutions from discovery and scoping through post-training, harness optimization, deployment, and production.
- Design evaluations, synthetic data pipelines, dataset strategies, post-training workflows, and success criteria for domain-specific AI.
- Apply LoRA/PEFT, supervised fine-tuning, synchronous and asynchronous reinforcement learning, and model and hyperparameter optimization.
- Tune prompting, tool use, orchestration, and context management for LLM and agentic systems.
- Optimize distributed inference and training workloads for memory efficiency, throughput, latency, and scaling across multi-GPU and multi-node systems.
- Scope technical engagements, shape statements of work, and lead delivery with partners and customers.
- Build reusable recipes, reference pipelines, and playbooks that enable partners to adopt open models independently.
- Collaborate with product, research, and engineering teams to incorporate partner and customer insights into NVIDIA models and software.
Requirements
- Bachelor’s, Master’s, or PhD in Computer Science, Engineering, Machine Learning, or a related field, or equivalent experience.
- 8+ years of experience in ML or software engineering, applied AI, forward deployed engineering, or solutions architecture, including 3–5+ years of hands-on LLM post-training and production experience.
- Deep expertise in LoRA/PEFT, supervised fine-tuning, reinforcement learning, deep learning, machine learning, model architectures, and hyperparameters.
- Experience with large-scale distributed training, inference performance optimization, multi-GPU systems, and multi-node systems.
- Hands-on experience with synthetic data pipelines, dataset curation and filtering, evaluation sets, and harness engineering for LLM and agentic systems.
- Proficiency in PyTorch, Hugging Face Transformers, Python, and Linux.
- Experience scoping engagements, shaping statements of work, and leading delivery with partners and customers.
- Strong communication, problem-solving, organizational, relationship-building, and cross-functional decision-making skills.
- Preferred experience with Nemotron, Cosmos, open models, Tinker APIs, NVIDIA NeMo, Megatron, multimodal or world-foundation-model post-training, large GPU clusters, SLURM, or Kubernetes.
Benefits
- Base salary ranges from 184,000 USD to 287,500 USD for Level 4 and from 224,000 USD to 356,500 USD for Level 5, depending on location, experience, and comparable employee pay.
- Eligible for equity and benefits.
- Applications accepted at least until October 22, 2026.
Tech Stack
Categories
AI ApplicationsForward Deployed
About Nvidia
Nvidia designs and sells GPUs and accelerated computing platforms for data centers, AI/ML, graphics, gaming, and automotive, monetizing through hardware, software platforms (CUDA, AI frameworks), and systems like DGX and networking. Customers include cloud providers, enterprises, researchers, and OEMs. Founded in 1993 and headquartered in Santa Clara, it is a public company traded on NASDAQ under NVDA.