Senior GenAI Technical Lead, Partner Platforms

🕒 il y a 1 mois

🏄 California – Distant

🏄 California – Remote

💵 $184 000 - $356 500 / an

⏰ Temps Plein

🟠 Senior

🧑‍💻 Développeur Full-Stack

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NVIDIA

Site WebLinkedInTous les Emplois

10 000+ employés

Fondée en 1993

🤖 Intelligence artificielle

🎮 Jeux vidéo

Artificial Intelligence • Gaming • Automotive

NVIDIA est une entreprise technologique de premier plan, spécialisée dans le calcul accéléré et l’intelligence artificielle (IA). NVIDIA est à l’avant‑garde des avancées en GPU (processeurs graphiques), cloud computing, centres de données et réalité virtuelle, avec un accent particulier sur les secteurs du gaming, de l’automobile, de la santé et de la robotique. Ses innovations, telles que NVIDIA Omniverse, transforment les processus numériques traditionnels en permettant des simulations haute fidélité et des tâches de rendu de pointe. Ses applications couvrent de nombreux secteurs, des véhicules autonomes avec NVIDIA DRIVE aux solutions de santé avec NVIDIA Clara, ainsi que des analyses et workflows pilotés par l’IA.

Description

• Build and drive the technical integration of our GenAI offerings across a focused set of ISV and CSP Platforms, collaborating closely with their Platform Architects. • Define technical objectives, timelines, and product adoption strategy, aligning with each partner’s long-term business objectives. • Hands-on design and ship methodologies, code, and reference architectures that bring RAG, LLM inference, and Multi-Agent workflows to life using NVIDIA libraries (NeMo, NIMs, Triton, Tensor-RT, etc.) as well as vLLM, LangChain, vector DBs, MCP, A2A, and related technologies, deployed across major CSP platforms such as AWS, Azure, GCP, etc. • Own the technical product engagement. • Drive regular meetings, progress tracking, adoption status, and internal reporting consistent with NVIDIA's culture. • You will work closely with NVIDIA Product, Engineering, Research, Solution Architecture, and other organizations to achieve the most efficient solution. • Develop understanding across all stages of GenAI lifecycle with depth in select areas such as Data Curation, LLM Pre-training, Finetuning such as PEFT, SFT, post-training, Reasoning, RAG, Multi-agent workflows and LLM Inference for production deployments. • Represent Partner needs and architecture design to Product and Engineering teams. • Contribute to Product roadmap by articulating insights from large-scale enterprise environments and cross-industry patterns, captured from ISV engagements. • Develop expertise in GenAI Platform Architecture and keep up to date with the latest in the industry and NVIDIA libraries, models, and frameworks to best support the partner Platform teams.

🎯 Exigences

• 8 + years of proven experience in technical Product or Engineering roles in Enterprise Software, Cloud Platforms, and production deployments with a focus on building partner integrations. • Masters or PhD in Computer Science, Electrical Engineering or equivalent experience. • Strong background in AI/ML and Deep Learning with hands-on experience building enterprise-grade GenAI systems such as intricate RAGs, Multi-Agent architectures, and production LLM deployments in a customer-facing role. • Experience with programming languages and libraries such as HuggingFace, LangChain, Python, PyTorch, NVIDIA NeMo, vLLM, AutoGen, TensorRT-LLM, etc. and LLM application stages such as Pre-training, Customization, Inference, Evaluation, and Benchmarking. • Ability to swiftly research, prototype, and collaborate with multiple teams to arrive at the best technical solution for new and evolving GenAI customer scenarios driving to completion, demonstrating collaboration and ownership of large projects. • Strong understanding of enterprise deployments including MLOps, Cloud Native technologies such as Kubernetes, Docker, Kubeflow, and Enterprise IT environments including Security, Compliance, Governance, Data infrastructure, and Deployments across on-prem, hybrid, and multi-cloud platforms. • Strong executive-caliber communication, and deep curiosity for emerging AI technologies. • High ownership and initiative, keeping internal and external collaborators aligned.

🏖️ Avantages

• equity • benefits