Senior Deep Learning Algorithm Engineer

NVIDIA
Santa Clara
Workplace: HybridFull timeUSD 184,000 - 356,500 annuallyFunction: Data Science & Machine LearningExperience: 5+ yearsEducation: mastersSkills: ["Collaboration","Performance analysis","Debugging","Research","Problem-solving"]

Design, develop, and optimize open-source, cloud-native AI frameworks for large language model (LLM) and multimodal foundation model training and post-training. Expand Megatron Core and NeMo Framework capabilities by implementing distributed training algorithms, model parallel paradigms, robust APIs, and performance tuning for next-gen NVIDIA GPUs. Collaborate with users, partners, and the open-source community to deliver end-to-end training, inference, evaluation, deployment, tooling, and scalable AI toolkits.

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FursaFursa
NVIDIA
NVIDIA
3 days ago

Senior Deep Learning Algorithm Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 1 hour agoStatus: Live
Reposted: similar role first listed 7 months ago

Job Summary

Design, develop, and optimize open-source, cloud-native AI frameworks for large language model (LLM) and multimodal foundation model training and post-training. Expand Megatron Core and NeMo Framework capabilities by implementing distributed training algorithms, model parallel paradigms, robust APIs, and performance tuning for next-gen NVIDIA GPUs. Collaborate with users, partners, and the open-source community to deliver end-to-end training, inference, evaluation, deployment, tooling, and scalable AI toolkits.
Location: Santa Clara
Workplace: Hybrid
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Develop algorithms for AI/DL, data analytics, machine learning, or scientific computing.
  • •Contribute to and advance open-source NeMo-RL, Megatron Core, and NeMo Framework.
  • •Solve large-scale end-to-end AI training and inference challenges across the model lifecycle.
  • •Innovate with model architectures, distributed training algorithms, and model parallel paradigms.
  • •Perform performance tuning and optimizations for training/fine-tuning with mixed precision on next-gen NVIDIA GPU architectures.

Pay and Benefits

Salary: USD 184,000 - 356,500 annually
Equity and Bonus:Equity

Key Requirements

  • •MS, PhD, or equivalent experience in Computer Science, AI, Applied Math, or related fields.
  • •5+ years of industry experience.
  • •Experience with AI frameworks (e.g., PyTorch, JAX, Ray) and/or inference/deployment environments (e.g., TRTLLM, vLLM, SGLang).
  • •Proficiency in Python, software design, debugging, performance analysis, and test design/documentation.
  • •Strong understanding of AI/deep-learning fundamentals and practical applications.
Experience:5+ yearsLarge language modelsReinforcement learningDistributed computing
Education:Master's
Skills:CollaborationPerformance analysisDebuggingResearchProblem-solving
Tech Stack:Megatron CoreNeMo FrameworkNeMo-RLPyTorchJAXRayTRTLLMVLLMSGLangPythonMixed precisionGPUDistributed trainingModel parallelism

Company Brief

NVIDIA
Designs and manufactures GPUs, AI accelerators, and system-on-chip products for gaming, data centers, professional visualization, and automotive markets, enabling advanced graphics, AI, and high-performance computing solutions worldwide.
Industry: Electronics Manufacturing
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: Santa Clara, United States
Founded: 1993
Glassdoor
Glassdoor: 4.3
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