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Nvidia Deep Learning Jobs in Virginia (NOW HIRING)

Our projects span multiple different data modalities and incorporate advanced algorithms, deep ... Experience running models on NVIDIA GPUs * Experience containerizing and deploying software using ...

Our projects span multiple different data modalities and incorporate advanced algorithms, deep ... Experience running models on NVIDIA GPUs * Experience containerizing and deploying software using ...

Our projects span multiple different data modalities and incorporate advanced algorithms, deep ... Experience running models on NVIDIA GPUs * Experience containerizing and deploying software using ...

Experience with physics-based simulators such as NVIDIA's Issac Sim is required. * Robotics ... Knowledge and Learning: You possess broad technical interests along with a deep knowledge of a ...

Senior Machine Learning Engineer

Mclean, VA

$105K - $145K/yr

About the Role We're seeking a Senior ML Engineer (Technical Lead) with deep hands-on expertise in ... Experiment tracking, Docker, ONNX/TensorRT, deploying inference services to the edge (e.g., NVIDIA ...

... algorithms and deep learning frameworks such as TensorFlow and PyTorch. • Demonstrated ... Nvidia GPU and C++ • Strong background developing / debugging • Experience in DevSecOps and ...

From learning to leadership, this is your chance to take your career to the next level. Our Senior ... NVIDIA, Amazon Web Services (AWS), Google Cloud Platform (GCP), or Microsoft Azure; one or more of ...

Nvidia Deep Learning information

See Virginia salary details

$10.9K

$83.2K

$138.8K

How much do nvidia deep learning jobs pay per year?

As of Jul 30, 2026, the average yearly pay for nvidia deep learning in Virginia is $83,166.00, according to ZipRecruiter salary data. Most workers in this role earn between $71,400.00 and $137,800.00 per year, depending on experience, location, and employer.

What is an Nvidia Deep Learning job?

An Nvidia Deep Learning job typically involves working with AI, machine learning, and deep learning technologies to develop, optimize, and deploy neural network models. Employees in these roles may work on GPU acceleration, AI frameworks like TensorFlow and PyTorch, and specialized hardware like NVIDIA GPUs and TensorRT. Positions can range from research scientists and software engineers to AI infrastructure specialists, focusing on improving model performance and scalability. These professionals contribute to cutting-edge AI applications in fields like autonomous vehicles, healthcare, and robotics.

What are the main challenges faced by professionals working in Nvidia Deep Learning roles?

Professionals in Nvidia Deep Learning positions often encounter challenges such as optimizing deep learning models to run efficiently on GPU architectures, keeping up with rapidly evolving AI frameworks, and troubleshooting complex system-level integration issues. They may also need to balance tight project deadlines with the demands of rigorous research and experimentation. Collaboration with interdisciplinary teams—such as software developers, data scientists, and hardware engineers—is common and essential to deliver robust solutions. Overcoming these challenges helps professionals stay at the forefront of innovation in the AI and deep learning industry.

What are the key skills and qualifications needed to thrive in the Nvidia Deep Learning position, and why are they important?

Excelling in an Nvidia Deep Learning role requires a strong background in computer science, machine learning, and mathematics, often supported by an advanced degree in a related field. Expertise in deep learning frameworks (such as TensorFlow or PyTorch), CUDA programming, and experience with Nvidia GPU hardware are typically expected, along with relevant certifications like Nvidia Deep Learning Institute credentials. Strong analytical thinking, problem-solving abilities, and effective teamwork distinguish top performers in this position. These skills are crucial to efficiently develop, optimize, and deploy deep learning models leveraging Nvidia technologies in cutting-edge applications.

What are the most commonly searched types of Nvidia Deep Learning jobs in Virginia? The most popular types of Nvidia Deep Learning jobs in Virginia are:
What job categories do people searching Nvidia Deep Learning jobs in Virginia look for? The top searched job categories for Nvidia Deep Learning jobs in Virginia are:
Infographic showing various Nvidia Deep Learning job openings in Virginia as of July 2026, with employment types broken down into 100% Full Time. Highlights an 74% In-person, and 26% Remote job distribution, with an average salary of $83,166 per year, or $40 per hour.

Senior Machine Learning Engineer

STR

Arlington, VA • On-site

$155K - $195K/yr

Other

Posted 15 days ago


Job description

About the Team:

STR's Intelligence Division researches and develops advanced analytics and machine learning-based solutions to solve challenging problems related to national security. Our team consists of passionate and motivated engineers with advanced degrees in engineering, computer science, mathematics, and data science, who are seeking opportunities to use their deep technical knowledge and creativity to tackle some of the hardest problems that our customers face. Our projects span multiple different data modalities and incorporate advanced algorithms, deep learning, and statistical techniques to uncover patterns in social media, structured and unstructured text, time series, geospatial, and imagery data, and must operate under challenging constraints not typically found in the commercial world. The tools and technologies we develop have real world impact and US Government analysts and operators use them to enable intelligence activities around the globe.

The Role

As a Senior Machine Learning Engineer, you will turn cutting-edge AI/ML research into production systems that solve critical national security problems.

Working as part of a multidisciplinary team of researchers, engineers, and domain experts, you will bridge the gap between prototype and product by hardening solutions, building scalable backend services, and creating polished user interfaces with intuitive workflows. You will build software with AI/ML at its core, ranging from classical statistical methods to frontier language models, deployed across a diverse set of platforms including cloud, onprem, desktop, mobile, and edge devices. In addition, you will collaborate closely with customers to understand mission needs, rapidly prototype capabilities, and iterate based on user feedback.

What You'll Do:

  • Partner directly with customers, stakeholders, and end users to translate mission needs into technical requirements and iterate based on real-world feedback
  • Drive technical excellence by providing leadership and championing software engineering best practices across multidisciplinary teams
  • Architect loosely coupled systems prioritizing interpretability, maintainability, and feature growth
  • Bridge the gap between research and production by implementing novel capabilities into existing live systems
  • Engineer robust backend services, scalable APIs, and optimized database models
  • Develop polished, intuitive, and responsive user interfaces in close collaboration with UI/UX designers
  • Orchestrate the deployment and maintenance of applications across cloud, desktop, mobile, and edge environments, including air-gapped systems
  • Build and optimize CI pipelines and manage execution runners to maintain code quality and reproducible builds
  • Contribute to the full software development lifecycle, including strategic project planning, rigorous code reviews, and comprehensive testing

Who you are:

  • Active Secret security clearance, for which U.S citizenship is needed by the U.S government
  • Enjoys working hard and seeing mission impact
  • BS degree in Computer Science, Software Engineering, Data Science, Statistics, Mathematics, Physics, or a related technical field
  • 6+ years of professional software engineering and/or machine learning research experience (or equivalent experience depending on degree)

Soft skills

  • Strong written and verbal communication skills, with the ability to explain complex technical concepts to both technical and nontechnical audiences
  • Demonstrated ability to collaborate effectively within crossfunctional teams, give and receive constructive feedback, and mentor others
  • Comfortable building from partial or ambiguous requirements and iterating quickly based on user feedback and changing mission needs

Technical Skills

  • Experience developing, training, and deploying machine/statistical learning models using modern Pythonbased frameworks
  • Experience running models on NVIDIA GPUs
  • Experience containerizing and deploying software using Docker, and on cloud platform
  • Experience designing and implementing REST APIs
  • Experience designing data models and working with relational databases
  • Fluency in Python and its ecosystem
  • Proficiency in at least one systemslevel language with manual or lowlevel memory management
  • Proficiency in HTML, CSS, and JavaScript (experience with a modern frontend framework such as Svelte or React is a plus)
  • Solid understanding of software engineering principles, including testing, scalability, observability, maintainability, and performance optimization

Pay Information
Full-Time Salary Range: $155,000 - $195,000

The salary range listed is based on external market data. Offers are based on factors, such as but not limited to, the candidate's experience, education, training, key skills/critical skills, security clearances, and prevailing market and business conditions.