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Freelance Nvidia Machine Learning Jobs in Washington

The Role As a Senior Machine Learning Engineer, you will turn cutting-edge AI/ML research into ... Experience running models on NVIDIA GPUs * Experience containerizing and deploying software using ...

The Role As a Senior Machine Learning Engineer, you will turn cutting-edge AI/ML research into ... Experience running models on NVIDIA GPUs * Experience containerizing and deploying software using ...

The Role As a Senior Machine Learning Engineer, you will turn cutting-edge AI/ML research into ... Experience running models on NVIDIA GPUs * Experience containerizing and deploying software using ...

The Role As a Senior Machine Learning Engineer, you will turn cutting-edge AI/ML research into ... Experience running models on NVIDIA GPUs * Experience containerizing and deploying software using ...

Senior Machine Learning Engineer

Mclean, VA

$105K - $145K/yr

Senior Machine Learning Engineer Location: McLean, VA (hybrid); occasional travel to Durham, NC and ... Experiment tracking, Docker, ONNX/TensorRT, deploying inference services to the edge (e.g., NVIDIA ...

Autonomy SME, Lead

Washington, DC · On-site

$62.25 - $85.50/hr

Responsibilities : • Design and train machine learning models for perception, object detection ... hardware, such as NVIDIA Jetson, GPUs, and embedded platforms • Experience with robotics ...

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Freelance Nvidia Machine Learning information

What are the key skills and qualifications needed to thrive as a Freelance Nvidia Machine Learning Engineer, and why are they important?

To thrive as a Freelance Nvidia Machine Learning Engineer, you need a strong background in machine learning principles, deep learning frameworks (such as TensorFlow or PyTorch), and proficiency in Python programming, often supported by a relevant degree or certifications. Familiarity with Nvidia hardware (GPUs), CUDA programming, and tools like Nvidia Deep Learning SDKs is essential for optimizing and deploying models efficiently. Exceptional problem-solving, self-management, and client communication skills help you deliver effective solutions and maintain successful freelance relationships. Mastery of these skills ensures you can build high-performance models, meet client expectations, and stay competitive in the rapidly evolving ML landscape.

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

AspectFreelance Nvidia Machine LearningFreelance Data Scientist
Required CredentialsKnowledge of Nvidia GPU architectures, CUDA programming, machine learning frameworksStatistics, programming, data analysis skills, often with similar certifications
Work EnvironmentProject-based, remote, often with tech companies or startupsProject-based or consulting, remote or on-site, across various industries
Industry UsageAI, deep learning, GPU-accelerated applicationsData analysis, predictive modeling, business insights

Freelance Nvidia Machine Learning specialists focus on GPU-accelerated AI projects using Nvidia technologies, while Freelance Data Scientists handle broader data analysis and modeling tasks. Both roles are in high demand for tech-driven projects but differ in technical focus and tools used.

What are some common challenges freelance Nvidia Machine Learning specialists face when working with clients remotely?

Freelance Nvidia Machine Learning specialists often encounter challenges such as ensuring compatibility between client hardware and Nvidia GPU requirements, effectively communicating technical needs and project progress to non-expert clients, and managing project timelines without in-person oversight. Additionally, freelancers may need to set up secure access to client data or cloud environments, which can require extra coordination. Proactively clarifying expectations, maintaining clear documentation, and staying current with Nvidia's latest tools (like CUDA, cuDNN, or TensorRT) are essential strategies for overcoming these challenges.

What does a Freelance Nvidia Machine Learning specialist do?

A Freelance Nvidia Machine Learning specialist is an independent contractor who uses Nvidia hardware and software platforms, such as CUDA and TensorRT, to develop, optimize, and deploy machine learning models. These professionals often work with clients to accelerate AI workloads, implement deep learning solutions, and leverage GPU computing for data processing tasks. Their projects may include computer vision, natural language processing, or other AI applications that benefit from Nvidia’s technology stack. Freelancers in this field need strong programming skills, familiarity with Nvidia SDKs, and experience optimizing models for high-performance computing environments.
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 Freelance Nvidia Machine Learning jobs? Cities in Washington with the most Freelance Nvidia Machine Learning job openings:

Senior Machine Learning Engineer

STR

Arlington, VA

$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.