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Remote Nvidia Deep Learning Jobs in Idaho (NOW HIRING)

Sony

$50/hr

Strong analytical and programming skills in deep learning using frameworks and tools for machine ... Working Location Location flexible (Tokyo, NYC, remote) The target hourly rate for this internship ...

Sony

$50/hr

Strong analytical and programming skills in deep learning using frameworks and tools for machine ... Working Location Location flexible (Tokyo, NYC, remote) The target hourly rate for this internship ...

Sony

$50/hr

Strong analytical and programming skills in deep learning using frameworks and tools for machine ... Working Location Location flexible (Tokyo, NYC, remote) The target hourly rate for this internship ...

Sony

$50/hr

Strong analytical and programming skills in deep learning using frameworks and tools for machine ... Working Location Location flexible (Tokyo, NYC, remote) The target hourly rate for this internship ...

Sony

$50/hr

Strong analytical and programming skills in deep learning using frameworks and tools for machine ... Working Location Location flexible (Tokyo, NYC, remote) The target hourly rate for this internship ...

Sony

$50/hr

Strong analytical and programming skills in deep learning using frameworks and tools for machine ... Working Location Location flexible (Tokyo, NYC, remote) The target hourly rate for this internship ...

Sony

$50/hr

Strong analytical and programming skills in deep learning using frameworks and tools for machine ... Working Location Location flexible (Tokyo, NYC, remote) The target hourly rate for this internship ...

Sony

$50/hr

Strong analytical and programming skills in deep learning using frameworks and tools for machine ... Working Location Location flexible (Tokyo, NYC, remote) The target hourly rate for this internship ...

Block

Strong foundations in modern machine learning, including deep learning, optimization ... Remote work, medical insurance, flexible time off, retirement savings plans, and modern family ...

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Remote Nvidia Deep Learning information

What is the difference between Remote Nvidia Deep Learning vs Remote Machine Learning Engineer?

AspectRemote Nvidia Deep LearningRemote Machine Learning Engineer
Required CredentialsDeep learning certifications, Nvidia GPU expertise, programming skills in Python and CUDAMachine learning certifications, Python, data analysis, model deployment skills
Work EnvironmentRemote, GPU-intensive tasks, AI research, model trainingRemote, data processing, model development, deployment
Industry UsageAI research labs, tech companies, autonomous vehiclesTech firms, finance, healthcare, e-commerce

Remote Nvidia Deep Learning focuses on developing AI models using Nvidia GPUs and CUDA, often in research or AI-specific roles. Remote Machine Learning Engineers work on building and deploying machine learning models across various industries. While both roles require programming and data skills, Nvidia Deep Learning emphasizes GPU expertise and AI research, whereas Machine Learning Engineers focus on broader model deployment and application.

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Cities in Idaho with the most Remote Nvidia Deep Learning job openings:

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Infographic showing various Remote Nvidia Deep Learning job openings in Idaho as of August 2026, with employment types broken down into 8% Internship, 67% Full Time, and 25% Contract. Highlights an 100% Remote job distribution.

Cyber Analyst current L, Q or TS mandatory REMOTE

Idaho Falls, ID • Remote

United Global Technologies
IT Services • 11 - 50 employees
Learn more about United Global Technologiesexternal

Full-time

Re-posted yesterday

Job description

Must have an active, not current, DOE L, Q or TS and above to be qualified

REMOTE

Qualifying individual must have a current “L” or “Q” clearance OR Top Secret

Qualifying individual “MUST” have the following skillsets:
  • Deep expertise in Splunk SPL, including advanced search commands, statistical functions, data models, and performance optimization
  • Hands-on experience with Splunk Enterprise Security, including correlation searches, risk-based alerting (RBA), notable events, and the ES framework
  • Working knowledge of the Splunk AI Toolkit (AITK) for building and applying ML-based detections
  • Experience with the Splunk App for Data Science and Deep Learning (DSDL), including custom model development and deployment
  • Strong understanding of the MITRE ATT&CK framework and detection engineering methodology
  • Familiarity with common attack techniques, log sources, and security data (EDR, network, cloud, identity, etc.)

4. Qualifying individual “NICE” to have the following skillsets:

  • Experience with detection-as-code practices and tools (Git, CI/CD pipelines)
  • Proficiency in Python for data processing and model development
  • Knowledge of SOAR platforms and detection automation
  • Relevant certifications (Splunk Certified Power User/Admin, Splunk Enterprise Security Certified Admin, GIAC, etc.)
  • Prior experience in a SOC, threat hunting, or incident response role

In this role, the selected candidate will design, build, and tune detections that identify malicious activity across our environment, working at the intersection of security analysis, data engineering, and machine learning. We're looking for a candidate that lives and breathes Splunk and gets excited about turning raw telemetry into high-fidelity alerts, we want to hear from you.

What the candidate is expected to perform:

  • Design, develop, and maintain detection content using Splunk Search Processing Language (SPL) to identify threats across diverse data sources
  • Build and tune correlation searches, notable events, and risk-based alerting within Splunk Enterprise Security (ES)
  • Leverage the Splunk App for Data Science and Deep Learning (DSDL) to develop machine learning models for anomaly detection and advanced threat identification
  • Apply the Splunk App for Anomaly Detection and the Splunk AI Toolkit (AITK) to develop statistical and ML-driven detections that go beyond signature-based approaches
  • Map detection coverage to the MITRE ATT&CK framework and identify gaps in visibility
  • Collaborate with threat intelligence, incident response, and SOC teams to translate emerging threats into actionable detections
  • Reduce false positives and alert fatigue through continuous tuning and detection lifecycle management
  • Develop and maintain detection-as-code workflows, including version control, testing, and CI/CD for detection content
  • Create documentation, runbooks, and detection specifications to support downstream analysts