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Remote Nvidia Machine Learning Jobs in Washington

Elder Research

Data Scientist (Remote)

Arlington, VA · On-site +1

Maintain current in emerging tools and techniques in machine learning, statistical modeling, and ... Washington DC Metro Area - Remote (candidates MUST BE located in the National Capital Region - DMV ...

Elder Research

Data Scientist (Remote)

Arlington, VA · On-site +1

Maintain current in emerging tools and techniques in machine learning, statistical modeling, and ... Washington DC Metro Area - Remote (candidates MUST BE located in the National Capital Region - DMV ...

Knexus

AI Software Engineer (Remote)

Vienna, VA · Remote

This is a fully remote position for candidates in the continental U.S., with work hours aligned to ... This role involves leveraging cutting-edge technologies, including GenAI and machine learning ...

ManTech

AI Engineer

Washington, DC · On-site +1

$141K - $236K/yr

In-depth knowledge of MLOps/LLMOps principles and full machine learning lifecycle management ... Familiarity with Ray, NVIDIA GPU ecosystems, or Vector databases. * Advanced degree (Master's or ...

Lateral Insights LLC

Senior AI/ML Engineer

Great Falls, VA · Remote

$105K - $145K/yr

... machine learning platforms, and practical experience operationalizing AI solutions from concept to production. Location: Vienna VA (We will consider Remote candidates within US Mainland on EST ...

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Remote Nvidia Machine Learning information

Can you work for NVIDIA remotely?

Remote Nvidia machine learning roles are available, with many positions allowing employees to work from home depending on the team and project requirements. Candidates typically need strong technical skills in machine learning, experience with Nvidia tools like CUDA, and may require specific certifications or hardware setup for remote work. Availability varies by role and location policies.

Which 5 jobs will survive AI?

Remote Nvidia Machine Learning roles are likely to persist as they require specialized skills in AI, deep learning, and GPU programming. Jobs involving complex problem-solving, creativity, and human interaction, such as data scientists, AI researchers, software engineers, cybersecurity specialists, and technical trainers, are expected to remain in demand despite AI advancements.

How much do NVIDIA machine learning engineers make?

NVIDIA machine learning engineers typically earn between $100,000 and $160,000 annually, depending on experience, location, and skill level. Senior roles or those with specialized expertise in deep learning and GPU programming can earn higher salaries, often exceeding $180,000. Compensation may also include bonuses and stock options in competitive tech environments.

Is it difficult to get hired at NVIDIA?

Getting hired for a remote Nvidia machine learning role can be competitive due to the company's high standards and specialized skill requirements. Candidates typically need strong expertise in machine learning, deep learning frameworks, and relevant programming languages, along with a solid educational background. Demonstrating experience with Nvidia technologies and certifications can improve chances of selection.

What is the difference between Remote Nvidia Machine Learning vs Remote Data Scientist?

AspectRemote Nvidia Machine LearningRemote Data Scientist
Required CredentialsDeep learning, GPU programming, Nvidia certificationsStatistics, programming, data analysis
Work EnvironmentFocus on GPU-accelerated ML models, Nvidia toolsData analysis, modeling, visualization
Industry UsageAI, autonomous vehicles, gaming, HPCBusiness analytics, research, finance

Remote Nvidia Machine Learning specialists focus on developing GPU-accelerated AI models using Nvidia technologies, often requiring specific certifications and expertise in GPU programming. In contrast, Remote Data Scientists analyze data, build predictive models, and interpret results across various industries. While both roles involve data and programming skills, Nvidia Machine Learning roles are more specialized in GPU-based AI development, whereas Data Scientists have broader data analysis responsibilities.

What are the most commonly searched types of Nvidia Machine Learning jobs in Washington? The most popular types of Nvidia Machine Learning jobs in Washington are:
What cities in Washington are hiring for Remote Nvidia Machine Learning jobs? Cities in Washington with the most Remote Nvidia Machine Learning job openings:
Remote Nvidia Machine Learning jobs near you
Machine Learning Modeling and Simulation Engineer

Machine Learning Modeling and Simulation Engineer

SAIC

Chantilly, VA • On-site, Remote

Full-time

Posted 10 days ago

SAIC rating

7.9

Company rating: 7.9 out of 10

Based on 79 frontline employees who took The Breakroom Quiz

66th of 206 rated it services

Job description

Job ID: 2611773

Location: Chantilly, VA, US

Date Posted: 2026-04-22

Category: Engineering and Sciences

Subcategory: Modeling/Sim Engr

Schedule: Full-Time

Shift: Day Job

Travel: No

Minimum Clearance Required: TS.SCI_wPoly

Clearance Level Must Be Able to Obtain: None

Potential for Remote Work: ORA_ON_SITE


Description

SAIC has need for a Machine Learning Modeling and Simulation Engineer  to support a rapidly expanding Government Intelligence Community (IC) customer with cutting-edge programs within the National Reconnaissance Office (NRO) in Chantilly, VA.

Note:  The role offers a flexible work schedule, but we ask our team to be available for team meetings during core business hours (10:00 a.m. – 3:00 p.m.).

As the Machine Learning Modeling and Simulation Engineer, you will provide technical expertise across a variety of Machine Learning (ML) and Modeling and Simulation (M&S) topics, including developing and training ML models, designing simulation frameworks, conducting performance analyses, and applying data-driven approaches to solve complex problems. You will also assist with Systems Engineering topics (e.g., requirements, configuration management, readiness, verification and validation, etc.) to ensure seamless integration of ML capabilities within simulation environments. 

Job Duties to include:

  • Develop and maintain physics-based simulation models of spacecraft systems, including structures, sensors, and mission environments.
  • Perform end-to-end performance modeling for satellite missions, integrating sensor, orbital, and environmental models.
  • Conduct sensor phenomenology studies, including optical, infrared, or radar modeling for detection, tracking, and signature analysis.
  • Perform orbital mechanics modeling including orbit determination, orbital maneuvering, and spacecraft flight dynamics.
  • Use scripting languages (Python, MATLAB, or similar) to automate workflows, perform data analysis, and interface between simulation tools.
  • Apply Artificial Intelligence/Machine Learning (AI/ML) techniques (e.g., supervised/unsupervised learning, reinforcement learning, predictive modeling) to enhance simulation fidelity and performance.
  • Develop AI/ML models to analyze and predict satellite system behaviors, performance metrics, and mission outcomes based on simulation data.
  • Design and implement algorithms for anomaly detection, predictive maintenance, and optimization of satellite operations.
  • Use statistical and machine learning techniques to analyze data, identify patterns, and uncover insights relevant to satellite systems.
  • Integrate AI/ML models into existing simulation frameworks and tools to enhance their capabilities.
  • Provide value-added judgment and offer strategic recommendations to the customer on program objectives, advanced technologies, and system enhancements. 
  • Produce highly detailed, practical, and consistent deliverables that align with the organization’s mission and objectives, with a focus on innovation and cutting-edge solutions in machine learning and simulation. 

Qualifications

Required Education and Experience:

  • Bachelor's Aerospace Engineering, Mechanical Engineering, Physics, and five (5) years or more experience; Masters and three (3) years or more experience; PhD and 0 years related experience. 
  • Active Top Secret/SCI w/Poly Clearance.
  • 3+ years of experience in modeling and simulation for aerospace or space systems.
  • Strong understanding of sensor phenomenology --such as optical, infrared, or radar systems --and associated modeling methods.
  • Intermediate Python programming experience, demonstrated through hands-on experience with tasks such as data manipulation, automation, and development of Python-based solutions. Experience with libraries such as NumPy, SciPy, pandas, and matplotlib is beneficial.
  • Ability to communicate technical results clearly in written and verbal formats.

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