NVIDIA

1 day ago

Senior Data Scientist

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 23 hours agoStatus: Live

Job Summary

Build and ship production-ready agentic, LLM-powered systems that automate NVIDIA’s networking engineering workflows. Partner with networking and silicon SMEs to turn domain knowledge into structured agent instructions, retrieval pipelines (RAG), and evaluation datasets. Develop offline/online evaluation infrastructure using golden sets and live telemetry, then analyze failures and data gaps to improve algorithms, features, and a reusable agent platform.

Location: Israel

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

Key Responsibilities

•Build and ship agentic systems with multi-agent coordination, long-horizon reasoning, and planning frameworks to improve networking and NW silicon efficiency.
•Develop domain-specific agents and retrieval pipelines (RAG) across product telemetry, development artifacts, and engineering knowledge bases.
•Partner with networking SMEs to translate rules of thumb into structured agent instructions, evaluation datasets, and feedback loops.
•Create evaluation infrastructure using offline golden sets and live telemetry to enable iteration, cost control, and safe rollout.
•Analyze agent failures and data gaps, then prototype improvements to features, algorithms, and system development, laying groundwork for a reusable agent platform.

Key Requirements

•PhD/MSc in CS, CE, Data Science, Statistics, or a related field (or equivalent experience).
•5+ years in applied ML/AI or large-scale systems, with 2+ years building agentic or LLM-powered applications in production environments.
•Proficiency in Python; hands-on experience with agentic frameworks such as LangChain, LangGraph, CrewAI, or similar.
•Hands-on fine-tuning experience across full-weight, LoRA, and PEFT methods, including scaling laws and advanced alignment techniques (RL, RLHF, RLAIF, KL-divergence regularization).
•Hands-on NLP experience including BERT, word embeddings, sequence models, and classical NLP pipelines, with strong ML foundations (supervised learning, feature engineering, model evaluation).

Experience:5+ yearsApplied ML/AILarge-scale systemsAgentic AILLM-powered applicationsNLPData engineering

Education:PhD / Doctorate

Skills:CommunicationCollaborationDocumentationDriving progress

Tech Stack:PythonLangChainLangGraphCrewAILLMAgentic frameworksRAGMulti-agent coordinationRetrieval pipelinesFine-tuningLoRAPEFTScaling lawsRLRLHFRLAIFKL-divergence regularizationBERTWord embeddingsSequence models

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: 4.3

Website LinkedIn Glassdoor

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NVIDIA

1 day ago

Senior Data Scientist

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 23 hours agoStatus: Live

Job Summary

Location: Israel

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

Key Responsibilities

•Build and ship agentic systems with multi-agent coordination, long-horizon reasoning, and planning frameworks to improve networking and NW silicon efficiency.
•Develop domain-specific agents and retrieval pipelines (RAG) across product telemetry, development artifacts, and engineering knowledge bases.
•Partner with networking SMEs to translate rules of thumb into structured agent instructions, evaluation datasets, and feedback loops.
•Create evaluation infrastructure using offline golden sets and live telemetry to enable iteration, cost control, and safe rollout.
•Analyze agent failures and data gaps, then prototype improvements to features, algorithms, and system development, laying groundwork for a reusable agent platform.

Key Requirements

•PhD/MSc in CS, CE, Data Science, Statistics, or a related field (or equivalent experience).
•5+ years in applied ML/AI or large-scale systems, with 2+ years building agentic or LLM-powered applications in production environments.
•Proficiency in Python; hands-on experience with agentic frameworks such as LangChain, LangGraph, CrewAI, or similar.
•Hands-on fine-tuning experience across full-weight, LoRA, and PEFT methods, including scaling laws and advanced alignment techniques (RL, RLHF, RLAIF, KL-divergence regularization).
•Hands-on NLP experience including BERT, word embeddings, sequence models, and classical NLP pipelines, with strong ML foundations (supervised learning, feature engineering, model evaluation).

Experience:5+ yearsApplied ML/AILarge-scale systemsAgentic AILLM-powered applicationsNLPData engineering

Education:PhD / Doctorate

Skills:CommunicationCollaborationDocumentationDriving progress

Company Brief

NVIDIA

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: 4.3

Website LinkedIn Glassdoor