NVIDIA

4 days ago

Senior AI and Machine Learning Specialist

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 22 hours agoStatus: Live

Job Summary

Design, build, and operate production AI systems spanning classical machine learning, computer vision, large language models, and agentic workflows. Own the full lifecycle from development and evaluation through deployment, observability, and continuous improvement. Create scalable architectures for inference, APIs, data flows, workflow orchestration, and reliability. Lead technical reviews, code reviews, mentoring, and establish development and validation practices to ensure quality, latency, efficiency, scalability, and cost.

Location: Israel

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

Key Responsibilities

•Lead the build and delivery of production AI systems across machine learning, computer vision, LLM, and agentic use cases.
•Build AI applications and agents with tool use, multi-step workflows, state management, and safe production operation.
•Develop evaluation strategies, test suites, quality metrics, and production feedback loops for models and AI applications.
•Build scalable architectures including model serving, APIs, data flows, workflow orchestration, observability, security, and failure recovery.
•Deploy, monitor, and continuously improve AI systems for quality, latency, efficiency, reliability, scalability, and cost, providing technical leadership through reviews and mentoring.

Key Requirements

•5+ years of experience in machine learning engineering, AI engineering, software engineering, platform engineering, or a comparable production-focused role.
•Bachelor's degree.
•Extensive knowledge in one or more areas including classical machine learning, computer vision, NLP, generative AI, or LLM applications.
•Strong system-design skills, including distributed systems, data-intensive applications, and cloud infrastructure.
•Practical understanding of production LLM inference, including latency/efficiency trade-offs, context windows, token usage, model selection, and cost management.

Education:Bachelor's

Skills:CommunicationCollaborationEngineering judgment

Tech Stack:LLMLarge language modelsNLPComputer visionTemporalPrefectCI/CDContainersMonitoringObservabilityAPIsDistributed systemsCloud infrastructureModel servingWorkflow orchestrationStructured outputsData flows

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

4 days ago

Senior AI and Machine Learning Specialist

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 22 hours agoStatus: Live

Job Summary

Location: Israel

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

Key Responsibilities

•Lead the build and delivery of production AI systems across machine learning, computer vision, LLM, and agentic use cases.
•Build AI applications and agents with tool use, multi-step workflows, state management, and safe production operation.
•Develop evaluation strategies, test suites, quality metrics, and production feedback loops for models and AI applications.
•Build scalable architectures including model serving, APIs, data flows, workflow orchestration, observability, security, and failure recovery.
•Deploy, monitor, and continuously improve AI systems for quality, latency, efficiency, reliability, scalability, and cost, providing technical leadership through reviews and mentoring.

Key Requirements

•5+ years of experience in machine learning engineering, AI engineering, software engineering, platform engineering, or a comparable production-focused role.
•Bachelor's degree.
•Extensive knowledge in one or more areas including classical machine learning, computer vision, NLP, generative AI, or LLM applications.
•Strong system-design skills, including distributed systems, data-intensive applications, and cloud infrastructure.
•Practical understanding of production LLM inference, including latency/efficiency trade-offs, context windows, token usage, model selection, and cost management.

Education:Bachelor's

Skills:CommunicationCollaborationEngineering judgment

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