Senior AI Systems and Algorithms Engineer

Nvidia

Confirmed live today High trust

Hybrid

Quick summary

Work type: Hybrid
Location: Santa Clara, CANYVACONJCA
Salary: $152,000–$241,500 / yr
Employment: Full-time
Posted: 2 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $198k

This role $197k

$141k $252k

below market most similar roles pay here above market

This role pays more than 58% of similar roles. Most pay $160,812–$235,750 — the blue band above. At the midpoint, this role pays about $197k versus about $198k for comparable roles.

Based on 240 similar postings.

Employer

About Nvidia

Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing

Nvidia currently has 1792 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 1179 roles with salary data.

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At a glance

TL;DR · Senior AI Systems and Algorithms Engineer

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The Senior AI Systems and Algorithms Engineer joins the team to advance foundation model development, training, and deployment. This role covers the entire GenAI lifecycle, from large-scale data preparation to inference optimization and framework development. You will design scalable systems for multimodal dataset preparation, develop algorithms to improve pre-training efficiency, and advance techniques for efficient serving across cloud and edge platforms. Key responsibilities include contributing to open-source AI infrastructure and designing new algorithms for large-scale distributed training. Required skills include Python, PyTorch, and deep learning optimization. You will work with technologies such as Megatron-LM, Megatron Bridge, and NeMo-RL, focusing on reinforcement learning, model compression, quantization, and distributed training strategies like FSDP and various parallelism types to solve complex large-scale AI workload problems.

Skills

Python PyTorch Megatron-LM NeMo-RL Hugging Face Transformers Distributed Training Reinforcement Learning LLM VLM Quantization Model Compression FSDP TP/PP/CP/DP SFT PPO GRPO Inference Optimization Deep Learning Machine Learning

What you'll do

Design scalable systems for preparing high-quality multimodal datasets for frontier foundation model training.
Develop algorithms to improve the scalability, efficiency, and cost of large-scale pre-training and post-training.
Advance techniques to improve inference performance and reduce deployment costs across cloud and edge platforms.
Develop reusable infrastructure and contribute new model support to NVIDIA's open-source GenAI training platform.
Implement reinforcement learning techniques like PPO and GRPO for LLM and VLM post-training.
Apply model compression techniques including quantization, pruning, and knowledge distillation.
Optimize GPU performance and analyze latency/throughput for large-scale AI workloads.

What we're looking for

MS or Ph.D in Computer Science, AI, Applied Mathematics, or a related field (or equivalent experience).
5+ years of relevant industry experience.
Strong foundation in machine learning, deep learning, and optimization.
Excellent software engineering skills, including Python and PyTorch.
Experience building high-performance software for large-scale AI systems.
Strong analytical, debugging, and performance optimization skills.
Excellent communication and collaboration skills.
Experience in distributed training, LLM/VLM post-training, inference efficiency, or open-source AI infrastructure (preferred).

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