2

Remote Nvidia Machine Learning Jobs in Washington, DC

Machine Learning Engineer Schedule: Full-Time Shift: Day Job Travel: Yes - 10% of the time Minimum ... None Potential for Remote Work: ORA_HYBRID Description We are seeking to build a team of AI/ML ...

Machine Learning Engineer Schedule: Full-Time Shift: Day Job Travel: Yes - 10% of the time Minimum ... None Potential for Remote Work: ORA_HYBRID Description We are seeking to build a team of AI/ML ...

Autonomy SME, Lead

Washington, DC · On-site +1

$116K - $152K/yr

Remote Work: Hybrid Job Number: R0243516 Location: Washington,DC,US Share job via: Share Autonomy ... Design and train machine learning models for perception, object detection, tracking, and ...

... challenges using machine learning, computer vision, predictive analytics, generative AI, and ... The team combines Applied AI Specialists, strategic ecosystem partners such as NVIDIA, and Forward ...

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 ...

Showing results 41-60

Remote Nvidia Machine Learning information

See Washington, DC salary details

$28.9K

$48.2K

$99.7K

How much do remote nvidia machine learning jobs pay per year?

As of Sep 10, 2026, the average yearly pay for remote nvidia machine learning in Washington, DC is $48,230.00, according to ZipRecruiter salary data. Most workers in this role earn between $36,800.00 and $52,100.00 per year, depending on experience, location, and employer.

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, DC?

The most popular types of Nvidia Machine Learning jobs in Washington, DC are:

AI Machine Learning Developer Principal

Chantilly, VA • On-site, Remote

SAIC
IT Services • 10K+ employees

$160K - $200K/yr

Full-time

Posted 6 days ago


SAIC rating

7.6

Company rating: 7.6 out of 10

Based on 81 frontline employees who took The Breakroom Quiz


Job description

Job ID: 2616563

Location: Chantilly, VA, US

Date Posted: 2026-09-04

Category: Engineering and Sciences

Subcategory: Machine Learning Engineer

Schedule: Full-Time

Shift: Day Job

Travel: Yes - 10% of the time

Minimum Clearance Required: TS.SCI

Clearance Level Must Be Able to Obtain: None

Potential for Remote Work: ORA_HYBRID


Description

We are seeking to build a team of AI/ML Developers to join our Solutions and Technology Group, reporting to the Intel Space CTO. In this matrixed role, you will lead the creation, prototyping, and operationalization of cutting-edge Artificial Intelligence and Machine Learning (AI/ML) Proof of Concepts (PoCs) specifically tailored for Intelligence Community (IC) mission use cases.

This is a dynamic, high-impact set of positions supporting multiple programs. You will operate as a shared technical subject matter expert, balancing intermixed timelines, competing program priorities, and evolving delivery expectations. The ideal candidates excels at rapid prototyping, taking complex concepts and turning them into functional demonstrations. This is a hybrid opportunity and are open to candidates in Chantilly or NOVA. Candidates must have an active TS/SCI clearance. 

1. Rapid PoC & Demo Prototyping (40%)

  • Design & Build: Rapidly design, build, and deploy high-fidelity, visual AI/ML prototypes (GenAI/LLMs, NLP, computer vision, predictive analytics) to address complex IC mission needs. The PoCs can be either on the unclassified side or on-prem in a SCIF.
  • Mission Alignment: Collaborate with program leads and stakeholders to align prototypes with real-world user workflows and emerging technical requirements.

2. Operationalization & MLOps Integration (30%)

  • Secure Deployment: Transition sandboxed PoCs into secure, multi-tenant cloud environments (AWS C2S, Azure Secret) and air-gapped networks.
  • Pipeline Engineering: Build automated CI/CD pipelines, containerize applications, and ensure compliance with federal software assurance and security standards.

3. Matrixed Program Support & Timeline Management (20%)

  • Cross-Program Execution: Successfully divide technical execution across multiple active programs with distinct, overlapping deliverable timelines.
  • Priority Coordination: Proactively negotiate schedules with multiple Project Managers to ensure all high-priority milestones are met.

4. Technical Communication & Stakeholder Engagement (10%)

  • Demos & Docs: Conduct compelling live technical demonstrations for senior IC customers and maintain clean, reusable codebases and architectural documentation.

Qualifications

  • Bachelor’s degree in Computer Science, Data Science, Engineering, or a related technical discipline with 9+ years of relevant experience; OR Master’s degree with 7 years of relevant experience.
  • Candidates must be U.S. Citizens.
  • Clearance: Active TS/SCI (or ability to immediately upgrade from TS if SCI was held within the last 3 years).
  • Programming Skills: Proficiency in Python and software engineering practices (version control with Git, unit testing, clean code architectures).
  • Foundational AI/ML Frameworks: Hands-on experience developing ML models using frameworks like PyTorch or TensorFlow, and handling structured/unstructured data.

Preferred Qualifications:

  • Experience deploying AI/ML models in secure, multi-tenant cloud environments (e.g., AWS C2S / SC2S, Azure Government) or air-gapped networks.
  • Familiarity with MLOps and orchestration platforms (e.g., MLflow, Kubeflow, Apache Airflow, Triton Inference Server).
  • Experience using lightweight frontend tools (e.g., Streamlit, Gradio) to build functional, interactive user interfaces for demonstrations.
  • Familiarity with IC missions.

Target salary range: $160,001 - $200,000. The estimate displayed represents the typical salary range for this position based on experience and other factors.

What SAIC employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom