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Freelance Nvidia Machine Learning Jobs in Washington

Autonomy SME, Lead

Washington, DC · On-site +1

$116K - $152K/yr

Design and train machine learning models for perception, object detection, tracking, and ... Experience building and deploying AI models on edge hardware, such as NVIDIA Jetson, GPUs, and ...

Design and train machine learning models for perception, object detection, tracking, and ... Experience building and deploying AI models on edge hardware, such as NVIDIA Jetson, GPUs, and ...

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Freelance Nvidia Machine Learning information

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 key skills and qualifications needed to thrive as a freelance Nvidia machine learning specialist?

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 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:

$112K - $257K/yr

Full-time

Medical, Life, Retirement, PTO

This job post has expired today. Applications are no longer accepted.


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Job description

Autonomy SME, Lead
The Opportunity:
As an Autonomy and UAS Engineer, you will design, develop, and deploy machine learning models that power intelligent behaviors on unmanned systems. You will work with advanced autonomy frameworks, including platforms such as Shield AI's Hivemind to build resilient navigation, perception, targeting, and collaborative autonomy capabilities.
You will operate at the cutting edge of edge AI, computer vision, reinforcement learning, and real-time embedded systems, helping the military transition from human-in-the-loop control to AI-assisted and autonomous mission execution.
As a technical lead, you will guide autonomy architecture decisions, mentor engineering teams, and support the integration of autonomy capabilities into operational military systems.
What You'll Work On:
  • Design and train machine learning models for perception, object detection, tracking, and classification.
  • Develop reinforcement learning and autonomy algorithms for navigation and mission execution.
  • Implement sensor fusion models combining EO, IR, LiDAR, GPS-denied navigation, and telemetry data.
  • Optimize AI models for deployment on edge compute platforms such as GPU, TPU, and embedded systems.
  • Develop and integrate autonomy behaviors within platforms such as Hivemind.
  • Implement mission planning logic and adaptive decision-making algorithms.
  • Enable collaborative autonomy between multiple UAS platforms.
  • Lead the design and implementation of autonomy architectures for UAS and multi-agent systems.
  • Build simulation-based training pipelines for autonomy validation.
  • Deploy containerized AI models to airborne and ground edge nodes.
  • Optimize inference latency and resource utilization.
  • Conduct hardware-in-the-loop (HIL) and software-in-the-loop (SIL) testing.
  • Develop secure software pipelines aligned to DoD cybersecurity standards.
  • Integrate AI outputs into tactical networks and mission command systems.
  • Implement CI/CD pipelines for rapid model iteration and field updates.
  • Provide technical leadership and mentorship to engineers developing autonomy capabilities.
  • Support flight testing, operational demonstrations, military exercises, and customer evaluations.
  • Collaborate with government stakeholders, operators, and engineering teams to define autonomy requirements and roadmaps.

Join us. The world can't wait.
You Have:
  • 5+ years of experience in software engineering, including AI/ML systems
  • Experience with Python and C++
  • Experience with deep learning frameworks, such as PyTorch, TensorFlow, and ONNX
  • Experience building and deploying AI models on edge hardware, such as NVIDIA Jetson, GPUs, and embedded platforms
  • Experience with robotics middleware, such as ROS or ROS2
  • Experience with computer vision or autonomous navigation systems
  • Experience leading technical teams, architecture decisions, or autonomy-focused development efforts
  • Experience integrating autonomous systems into operational, test, or simulation environments
  • Ability to obtain a Secret clearance
  • Bachelor's degree in a Computer Science, Robotics, Aerospace Engineering, or Electrical Engineering field

Nice If You Have:
  • Experience working in military exercises and war games
  • Experience with autonomy frameworks such as Hivemind, PX4, ArduPilot, NVIDIA Isaac, or ROS2
  • Experience with collaborative autonomy, swarming, or multi-agent mission execution
  • Ability to support flight testing and operational evaluations
  • Top Secret clearance
  • Master's degree
  • ML, AI, or Solution Architecture Certification

Clearance:
Applicants selected will be subject to a security investigation and may need to meet eligibility requirements for access to classified information.
Compensation
At Booz Allen, we celebrate your contributions, provide you with opportunities and choices, and support your total well-being. Our offerings include health, life, disability, financial, and retirement benefits, as well as paid leave, professional development, tuition assistance, work-life programs, and dependent care. Our recognition awards program acknowledges employees for exceptional performance and superior demonstration of our values. Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible to participate in Booz Allen's benefit programs. Individuals that do not meet the threshold are only eligible for select offerings, not inclusive of health benefits. We encourage you to learn more about our total benefits by visiting the Resource page on our Careers site and reviewing Our Employee Benefits page.
Salary at Booz Allen is determined by various factors, including but not limited to location, the individual's particular combination of education, knowledge, skills, competencies, and experience, as well as contract-specific affordability and organizational requirements. The projected compensation range for this position is $112,800.00 to $257,000.00 (annualized USD). The estimate displayed represents the typical salary range for this position and is just one component of Booz Allen's total compensation package for employees. This posting will close within 90 days from the Posting Date.
Identity Statement
As part of the hiring process, we will ask you to complete an identity verification process that leverages advanced biometrics and artificial intelligence to ensure authenticity and protect against identity fraud. You are expected to be on camera during interviews and assessments. We reserve the right to take your picture to verify your identity and prevent fraud.
Candidate AI Usage Policy
AI is a part of our daily work at Booz Allen, and we are committed to the responsible and ethical use of AI tools. However, we want to ensure a fair candidate process based on your own skills and knowledge. As part of this commitment, the use of artificial intelligence (AI) or other tools to assist with responses during interviews (whether in-person or virtual) is prohibited unless permission is explicitly provided.
Work Model
Our people-first culture prioritizes the benefits of collaboration, whether it occurs in person or virtually. To support engagement and effective communication, employees working virtually are generally expected to have their cameras on during meetings.
  • Remote: If this position is listed as remote, there may still be occasions when you are required to work in person at a Booz Allen or customer facility.
  • Hybrid: If this position is listed as hybrid, you will be expected to work from a Booz Allen facility frequently, in alignment with leadership expectations and the needs of the role. You may also be required to work from or visit a customer facility.
  • Onsite: If this position is listed as onsite, work will primarily be performed at a Booz Allen office or customer facility, where employees will collaborate directly with colleagues and customers as required by the role.

Commitment to Non-Discrimination
All qualified applicants will receive consideration for employment without regard to disability, status as a protected veteran or any other status protected by applicable federal, state, local, or international law.

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About Booz Allen Hamilton

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Booz Allen Hamilton is a leading provider of management and technology consulting services to the US government in defense, intelligence, and civil markets. Headquartered in McLean, Virginia, the firm also serves major corporations, institutions, and not-for-profit organizations. Founded in 1914 by Edwin G. Booz, the company has a long-standing tradition of helping clients achieve success by delivering a wide range of consulting services that include strategic planning, human capital and learning, communication, systems development, and others. The company's mission is to empower people to change the world, and it has a reputation for maintaining the highest standards of integrity and-excellence.

Industry

It services

Company size

10,000+ Employees

Headquarters location

McLean, VA, US

Year founded

1914