Deep Learning Engineer, LLM Accuracy Evaluation

Poland

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Not SpecifiedCompensation

Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

Artificial Intelligence, Computer Hardware, Software DevelopmentIndustries

Requirements

Candidates must possess a BS, MS, or PhD in Computer Science, AI, Applied Math, or a related field, or equivalent experience. They should have over 10 years of hands-on experience in AI for natural language processing (NLP) and large language models (LLMs), with strong mathematical foundations and expertise in AI/DL algorithms. Excellent problem-solving, debugging, performance analysis, test design, and documentation skills are required, along with strong written and verbal communication abilities for both independent and collaborative work in a fast-paced environment. Experience in LLM accuracy evaluation, inference and deployment environments like TensorRT, ONNX, or Triton, MLOps practices, running large-scale workloads in HPC clusters, and proficiency in Linux environments and containerization technologies like Docker are considered advantageous.

Responsibilities

The Deep Learning Engineer will collaborate with partners and the open-source community to deliver flagship models as optimized NVIDIA Inference Microservices (NIM). They will research and develop innovative deep learning methodologies for evaluating new model families across diverse domains. Additionally, the engineer will analyze, influence, and enhance AI/DL libraries, frameworks, and APIs, ensuring consistency with best engineering practices. This role involves researching, prototyping, and building robust tools and infrastructure pipelines to support AI initiatives.

Skills

Deep Learning

LLM

RAG

Agents

Vision Models

Gemma

Llama-3

NVIDIA Inference Microservices (NIM)

GPU

Natural Language Processing (NLP)

Problem-solving

Debugging

Performance Analysis

Test Design

Documentation

AI/DL Algorithms

Mathematical Foundations

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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