Senior Software Engineer, AI Frameworks

🕒 il y a 2 mois

🏄 California – Distant

🏄 California – Remote

💵 $152 000 - $241 500 / an

⏰ Temps Plein

🟠 Senior

🧑‍💻 Développeur Full-Stack

🦅 Parrain de Visa H1B

Cette entreprise a parrainé des visas H1B par le passé.

Postuler Maintenant

Trouver des Emplois à Distance Similaires

Recevoir des emails pour des emplois à distance

📊 Vérifiez votre score de CV pour ce poste

Améliorez vos chances d'obtenir un entretien en vérifiant votre score de CV avant de postuler.

Télécharger le CV

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

• Design and implement end-to-end integrations of Grove with open-source AI frameworks (e.g., Dynamo, llm-d, Ray, PyTorch, and related ecosystem projects) • Build and maintain adapters, plugins, operators, and/or runtime components that enable Grove features to work smoothly across training and inference stacks • Partner with framework owners to upstream changes, contribute patches, and ensure long-term maintainability of integrations • Develop reference workflows, sample apps, and best-practice guides that accelerate adoption by users and partners • Optimize performance, scalability, and reliability for distributed training/inference, including multi-node and multi-GPU environments • Improve observability and operational readiness (metrics, logging, tracing, debugging tools) for Kubernetes-based deployments • Participate in technical design reviews, define APIs/contracts, and ensure compatibility across versions of frameworks and dependencies • Diagnose complex issues spanning containers, networking, scheduling, CUDA/GPU utilization, and framework runtime behavior.

🎯 Exigences

• BS/MS/PhD in Computer Science, Electrical Engineering, or related field (or equivalent experience) • 5+ years of proven experience in related field • Hands-on experience integrating with at least one major AI framework/runtime (e.g., PyTorch, Ray, Triton Inference Server ecosystem, distributed runtimes, model serving stacks) • Solid understanding of AI workloads: model development basics, training vs. inference tradeoffs, and performance considerations (throughput/latency, batching, memory) • Experience with distributed systems concepts (RPC, scheduling, fault tolerance, resource management) • Practical Kubernetes experience: deploying and operating services/jobs, Helm/Kustomize, operators/controllers (nice to have), and debugging clusters • Familiarity with containers and cloud-native tooling (Docker, container registries, CI/CD pipelines) • Strong software engineering experience in Go, C++ and/or Python, with a track record of shipping reliable systems • Strong interpersonal skills and ability to collaborate across teams and with open-source communities • Exceptional collaboration, communication, and documentation habits.

🏖️ Avantages

• equity • benefits