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Freelance Nvidia Machine Learning Jobs in Washington

Machine Learning Engineer

Centreville, VA · On-site

$102K - $144.38K/yr

Machine Learning Engineer II The Machine Learning Engineer II will be a member of the Learning and ... Familiarity with Nvidia Tools (CUDA, JetPack, TensorRT) and deployment process to Nvidia GPUs

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Machine Learning Engineer Company: Heven AeroTech Location: Sterling, Virginia FLSA: Exempt About ... Edge hardware deployment (NVIDIA Jetson, Google Coral TPU) * Embedded Linux and ROS experience

Machine Learning Engineer Company: Heven AeroTech Location: Sterling, Virginia FLSA: Exempt About ... Edge hardware deployment (NVIDIA Jetson, Google Coral TPU) * Embedded Linux and ROS experience

Machine Learning Engineer Company: Heven AeroTech Location: Sterling, Virginia FLSA: Exempt About ... Edge hardware deployment (NVIDIA Jetson, Google Coral TPU) * Embedded Linux and ROS experience

Senior Machine Learning Engineer

Mclean, VA · On-site

$107.20K - $147.20K/yr

Senior Machine Learning Engineer McLean, Virginia Senior Machine Learning Engineer Location: McLean ... Experiment tracking, Docker, ONNX/TensorRT, deploying inference services to the edge (e.g., NVIDIA ...

Senior Machine Learning Engineer

Mclean, VA · On-site

$105.60K - $145.10K/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 ...

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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 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 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 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 are popular job titles related to Freelance Nvidia Machine Learning jobs in Washington? For Freelance Nvidia Machine Learning jobs in Washington, the most frequently searched job titles 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:
Machine Learning Engineer

Machine Learning Engineer

Navstar

Centreville, VA • On-site

$102K - $144.38K/yr

Other

This job post has expired 1 day ago. Applications are no longer accepted.


Job description

Machine Learning Engineer II

The Machine Learning Engineer II will be a member of the Learning and Active Perception (LEAP) group in AV's MacCready Works division and support the development of a variety of innovative computer vision capabilities (object detection, classification, localization, and tracking) and other image/video analytics for defense and commercial applications. These development efforts require a range of skills and tools across traditional engineering, computer science, and mathematical disciplines including but not limited to data management, computer vision, machine learning, optimization, and deep neural networks. This position will span multiple stages of the development process including requirements gathering, algorithm design, prototyping, test and evaluation, and validation and verification testing. This role also involves support for experimentation and fielded systems requiring travel, both domestic and international.

Duties

  • Support development of computer vision and machine learning (ML) algorithms capable of object detection, classifying, localizing, and tracking objects of interest from a variety of stationary and mobile sensor platforms with the primary purpose of real-time automated target recognition (ATR)
  • Perform visual imagery data science to inform data collection, data labeling, and data selection for training deep computer vision ML algorithms, train the algorithms using the data, and validate data selection and algorithm design through a series of purpose-designed experiments. This includes:
    • Analyze ML algorithms to solve a given problem and rank them by their success probability on new data
    • Set objectives and develop models that help achieve them, along with metrics to track their progress
    • Select appropriate datasets and data representations
    • Analyze errors of the data, model, and design strategies to overcome them
  • Write and test software to support the integration of machine learning algorithms into aircraft (such as autopilots, payloads, or other functional components) or other systems
  • Other duties as assigned

Basic Qualifications (Required Skills & Experience)

  • BS in Computer Vision and Machine Learning is required or equivalent combination of education, training, and experience - with qualifications in any of the following fields: Mathematics, Optimization, Computer Science/Engineering, Electrical Engineering, Aerospace, or Mechanical Engineering
  • Minimum of 2 - 5 years' experience, and 2+ years of relevant experience in machine learning and/or computer vision
  • Proficiency with a deep learning framework, preferably PyTorch
  • Proficiency with basic libraries for machine learning such as, Open-CV, scikit-learn, and pandas
  • Familiarity with Linux
  • Familiarity with Nvidia Tools (CUDA, JetPack, TensorRT) and deployment process to Nvidia GPUs
  • Demonstrated ability to troubleshoot complex systems and perform algorithmic optimization
  • Ability to perform exploratory data analysis, including visualizing and manipulating large datasets

Other Qualifications & Desired Competencies)

  • Must be a team player and collaborate effectively
  • Excellent verbal and written skills
  • Has effective problem-solving, analytical and interpersonal skills
  • Ability to work within defined requirements to complete tasks under moderate supervision
  • Able to excel in a fast-paced, deadline-driven environment, where small teams share a broad variety of duties
  • Displays strong initiative and drive to accomplish goals and meet company objectives
  • Takes ownership and responsibility for current and past work products, and demonstrates a willingness to share the results with other team members and provide feedback and input to teammates working similar problems.
  • Is committed to learning from mistakes and driven to improve and enhance performance of oneself, others, and the company
  • Familiarity with office software and computer-based productivity tools

Special Requirements

  • U.S. Citizenship required
  • Ability to obtain (at minimum) a Secret level DoD security clearance
  • Willingness to travel (Occasionally / up to 20%)

Physical Demands

  • Ability to work in an office and manufacturing environment (Constant)
  • Required to sit and stand for long periods; talk, hear, and use hands and fingers to operate a computer and telephone keyboard (Frequent)

Clearance Level No ClearanceThe salary range for this role is: $102,000 - $144,375