Senior Deep Learning Engineer, Deep Learning Algorithms at NVIDIA

Warsaw, Woj. Mazowieckie, Poland

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Artificial Intelligence, TechnologyIndustries

Requirements

3+ years of experience in DL model implementation and SW Development
BSc, MS or PhD degree in Computer Science, Computer Architecture or related technical field
Excellent Python programming skills
Extensive knowledge of at least one DL Framework (PyTorch, TensorFlow, JAX, MxNet) with practical experience in PyTorch required
Strong problem solving and analytical skills
Algorithms and DL fundamentals
Docker containerization fundamentals

Responsibilities

Implement deep learning models from multiple data domains (CV, NLP/LLMs, ASR, TTS, RecSys and others) in multiple DL frameworks (PyT, JAX, TF2, DGL and others)
Implement and test new SW features (Graph Compilation, reduced precision training) that use the most recent HW functionalities
Analyze, profile, and optimize deep learning workloads on state-of-the-art hardware and software platforms
Collaborate with researchers and engineers across NVIDIA, providing guidance on improving the design, usability and performance of workloads
Lead best-practices for building, testing, and releasing DL software
Contribute to creation of large scale benchmarking system, capable of testing thousands of models on vast diversity of hardware and software stacks

Skills

Key technologies and capabilities for this role

PythonPyTorchJAXTensorFlowDGLDeep LearningGPU ArchitecturePerformance OptimizationGraph CompilationReduced Precision TrainingComputer VisionNLPLLMsASRTTSRecommendation Systems

Questions & Answers

Common questions about this position

What education is required for this Senior Deep Learning Engineer role?

A BSc, MS or PhD degree in Computer Science, Computer Architecture or related technical field is required.

What are the key required skills for this position?

The role requires 3+ years of experience in DL model implementation and SW Development, excellent Python programming skills, extensive knowledge of at least one DL Framework with practical experience in PyTorch required, strong problem solving and analytical skills, algorithms and DL fundamentals, and Docker containerization fundamentals.

What experience will help me stand out for this role?

Experience in performance measurements and profiling, containerization technologies such as Docker, GPU programming (CUDA or OpenCL), knowledge of DevOps/MLOps practices, and experience with CI systems like GitLab will make you stand out.

What is the company culture like at NVIDIA for this team?

NVIDIA has some of the most brilliant and forward-thinking people, values creative and autonomous individuals, and is an equal opportunity employer that values diversity.

Is this a remote position or does it require office work?

This information is not specified in the job description.

NVIDIA

Designs GPUs and AI computing solutions

About NVIDIA

NVIDIA designs and manufactures graphics processing units (GPUs) and system on a chip units (SoCs) for various markets, including gaming, professional visualization, data centers, and automotive. Their products include GPUs tailored for gaming and professional use, as well as platforms for artificial intelligence (AI) and high-performance computing (HPC) that cater to developers, data scientists, and IT administrators. NVIDIA generates revenue through the sale of hardware, software solutions, and cloud-based services, such as NVIDIA CloudXR and NGC, which enhance experiences in AI, machine learning, and computer vision. What sets NVIDIA apart from competitors is its strong focus on research and development, allowing it to maintain a leadership position in a competitive market. The company's goal is to drive innovation and provide advanced solutions that meet the needs of a diverse clientele, including gamers, researchers, and enterprises.

Santa Clara, CaliforniaHeadquarters

1993Year Founded

$19.5MTotal Funding

IPOCompany Stage

Automotive & Transportation, Enterprise Software, AI & Machine Learning, GamingIndustries

10,001+Employees

Benefits

Company Equity

401(k) Company Match

Risks

Increased competition from AI startups like xAI could challenge NVIDIA's market position.

Serve Robotics' expansion may divert resources from NVIDIA's core GPU and AI businesses.

Integration of VinBrain may pose challenges and distract from NVIDIA's primary operations.

Differentiation

NVIDIA leads in AI and HPC solutions with cutting-edge GPU technology.

The company excels in diverse markets, including gaming, data centers, and autonomous vehicles.

NVIDIA's cloud services, like CloudXR, offer scalable solutions for AI and machine learning.

Upsides

Acquisition of VinBrain enhances NVIDIA's AI capabilities in the healthcare sector.

Investment in Nebius Group boosts NVIDIA's AI infrastructure and cloud platform offerings.

Serve Robotics' expansion, backed by NVIDIA, highlights growth in autonomous delivery services.

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