Director, Forward Deployed Engineering - Open Models
NVIDIA is hiring a Director, Forward Deployed Engineering - Open Models in Santa Clara, United States. It pays $320k-$489k a year and Level rates it ; you can apply on Level.
Level's read on this job
- Level rates this forward deployed engineer role Builds AI ●●●●: the job is building AI systems.
- The listed pay starts 76% above the typical forward deployed engineer posting on Level.
- Tools and skills the posting cites include Nvidia Nemotron and Nvidia Cosmos.
- Level lists 2,700+ other open roles at NVIDIA.
- The role was posted in the last few days.
AI in this role
Founding Director of Forward Deployed Engineering for open AI models, leading technical strategy and partner ecosystem delivery.
Do you want to help the world build custom AI at scale? We’re hiring a founding Director to build and lead NVIDIA’s Forward Deployed Engineering organization for open models, including NVIDIA Nemotron and NVIDIA Cosmos, across North America. The mission is to turn open models into production-ready AI tuned to a specific domain, delivered through our partner ecosystem. We want any organization to build, own, and run its own AI on open source models, and this organization helps the ecosystem get there!
Unlike most forward deployed organizations, ours works primarily through NVIDIA’s partner ecosystem. Our FDEs work side by side with top partner engineering and research teams, co-lead joint customer engagements, and build the recipes and playbooks that help partners succeed and scale. This leader sets the strategy for North America, builds the organization, and carries the vision to partners, customers, and NVIDIA leadership. Are you an exceptional technical leader with deep roots in open model post-training and agent harness engineering, ready to build a world-class FDE organization? We’d love to meet you.
What you’ll be doing:
- This role sets the strategy and leads the team that delivers custom AI to end customers through NVIDIA’s partner ecosystem. The team deepens partner relationships and leads three-way engagements among NVIDIA, the partner, and the end customer. Our goal is hundreds of end customers running domain-specific Nemotron or Cosmos in production, supported by a strong ecosystem that delivers it.
- Hire and develop FDE leads, managers, and senior engineers across North America, and set a high bar for technical depth and customer impact. Create clear paths for growth and a team structure that scales with the ecosystem.
- The work stays technical. Set the technical direction for post-training, evaluation, harness engineering, and inference optimization, and be the person the team turns to on the hardest engagements. Keep up with the open model, post-training, and agents landscape, and bring new use cases and partner opportunities forward before partners ask.
- Partners are how we reach customers at scale. Build trusted relationships with leaders at partner and end-customer companies, shape joint plans and agreements, and see three-way engagements through to production. Set clear goals and track the results: partners adopting Nemotron, customers running in production, and customers willing to speak publicly. We help partners succeed on their own with reusable recipes, reference pipelines, and playbooks, so more developers can build domain-specific AI.
- We connect NVIDIA’s model research to partner and customer use cases. Work with Product, Research, and Engineering to bring what we see in the field back into Nemotron, Cosmos, and our software stack, and share what works with FDE leaders in other regions. Align priorities and resources with sales, partner, and solutions leaders, keep senior leadership informed on progress, and speak on NVIDIA domain-specific open models.
- Above all, we’re excited to help organizations worldwide build, own, and run their own AI on open source models!
What we need to see:
- Bachelor’s, Master’s, or PhD in Computer Science, Engineering, Machine Learning, or a related field, or equivalent experience.
- 14+ overall years in ML or software engineering, applied AI, FDE, or solutions architecture, including 8+ years leading technical teams and 5+ years of hands-on LLM post-training with models taken to production.
- A track record of building and scaling technical organizations across multiple locations and time zones, including managing managers or leads, and setting goals and measuring results for a customer-facing technical team.
- Deep technical credibility in post-training (LoRA/PEFT, SFT, and synchronous and asynchronous reinforcement learning), model architectures, synthetic data, and evaluation, plus agent harness engineering and optimization for LLM and agentic systems. Good understanding of large-scale distributed training and inference performance optimization across multi-GPU and multi-node systems.
- Deep understanding of the partner, open model, and cloud provider ecosystem, and where NVIDIA can add the most value. Proven ability to build alignment across multiple partners and customers on the same engagement, including at the executive level. Good understanding of how to drive ecosystem demand and match partners with customers.
- Proven ability to scope engagements, shape SOWs, and deliver consistently high quality across many engagements at once.
- Clear communication of complex technical ideas, from engineers to C-level executives. Excellent judgment, prioritization, and organizational skills, and comfort leading through ambiguity. Travel to partner and customer sites and NVIDIA offices up to [25%].
Ways to Stand Out from the Crowd:
- Experience building and scaling an FDE, applied research, or solutions organization from an early stage.
- History of building partner-led programs, ecosystems motions.
- Hands-on experience with Nemotron, Cosmos, and other open models, as well as serverless and self-managed post-training platforms (such as the Tinker API) and open-source frameworks such as NVIDIA NeMo and Megatron.
- A technical vision that influences product, engineering, and business decisions and drives production outcomes.
- Experience with multimodal or world-foundation-model post-training, and running training jobs on large GPU clusters with SLURM or Kubernetes with a passion for using AI tools to improve how the team builds, delivers, and scales.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until October 22, 2026.This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) 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.How we rate this
Director, Forward Deployed Engineering - Open Models at NVIDIA rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Pay
- This job starts at
- $320k
- Typical forward deployed engineer job
- $182k
This posting starts 76% above the typical forward deployed engineer job. See forward deployed engineer jobs
Questions you could be asked
- What's a project where you used Nvidia Nemotron hands-on?
- Walk me through how you've used Nvidia Cosmos in your day-to-day work.
- How would you decide a model or AI system is ready to ship?
- Tell me about a time a model underperformed in production. How did you find out, and what did you change?
Adapt your resume
- List these exact terms on your resume: Nvidia Nemotron and Nvidia Cosmos. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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