Senior Forward Deployed Engineer, Open Models
NVIDIA· Architect, Solutions
Santa Clara, CA$184k - $287.5kfull-timePosted 4d ago
About the role
Senior Forward Deployed Engineer driving technical engagement with partners and customers across NVIDIA's open model portfolio to turn open models into production-ready AI tuned to specific domains, from post-training through harness optimization.
Responsibilities
- Drive AI solutions from discovery and scoping through post-training, harness optimization, and deployment with partners and customers.
- Lead technical engagements by scoping work, shaping statements of work, and delivering with partner engineering teams and joint customers.
- Build reusable recipes, reference pipelines, and playbooks to scale partner success and ecosystem maturity.
- Connect model research to partner/customer use cases and bring field insights back into Nemotron, Cosmos, and the software stack.
- Design evaluations, build synthetic data pipelines, perform post-training with LoRA and other parameter-efficient methods, supervised fine-tuning, and reinforcement learning (synchronous and asynchronous).
- Tune harness (prompting, tool use, orchestration, context management) and optimize inference for production-cost efficiency.
- Support organizations worldwide in building, owning, and running AI on open source models.
Qualifications
- Bachelor's, Master's, or PhD in Computer Science, Engineering, Machine Learning, or related field, or equivalent experience.
- 8+ years in ML or software engineering, applied AI, FDE, or solutions architecture, including 3–5+ years hands-on LLM post-training and production.
- Solid fundamentals in deep learning and machine learning; deep expertise in post-training methods (LoRA/PEFT, SFT, RL) and trade-offs between RL synchronous and asynchronous approaches.
- Understanding of large-scale distributed training and inference performance optimization; ability to tune workloads for memory efficiency, throughput, latency, and scaling across multi-GPU/multi-node systems.
- Hands-on experience with post-training data (synthetic data pipelines, dataset curation/filtering, evaluation sets) and harness engineering for LLM/agentic systems.
- Proficiency in PyTorch, Hugging Face Transformers, Python, and Linux.
- Proven ability to scope engagements, shape SOWs, and lead delivery with partners/customers; strong organizational skills and ability to drive complex decisions across teams.
- Clear communication of complex technical ideas to engineers and executives; strong problem-solving, curiosity, and commitment to partner/customer success.
Skills
Required:Post-training methods (LoRA/PEFT, SFT, RL)Distributed training and inference optimizationHarness engineering for LLM/agentic systems
Benefits
- equity
- benefits (see NVIDIA benefits)
- base salary and equity opportunities
Last updated Oct 23, 2026. Interested? Apply on the company site.
About NVIDIA
World Leader in AI Computing
NVIDIA invents the GPU and drives advances in AI, HPC, gaming, creative design, autonomous vehicles, and robotics.
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