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Hourly Remote Machine Learning Engineer Jobs in Fairfax, VA

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Hourly Remote Machine Learning Engineer information

See Fairfax, VA salary details

$26.1K

$43.5K

$90K

How much do hourly remote machine learning engineer jobs pay per year?

As of Aug 19, 2026, the average yearly pay for hourly remote machine learning engineer in Fairfax, VA is $43,527.00, according to ZipRecruiter salary data. Most workers in this role earn between $33,200.00 and $47,000.00 per year, depending on experience, location, and employer.

What does an hourly remote machine learning engineer do?

An Hourly Remote Machine Learning Engineer is a professional who develops and implements machine learning models and algorithms for clients or employers on an hourly contract basis, all while working from a remote location. Their responsibilities typically include data preprocessing, model selection, training, testing, and deployment. They collaborate with teams via online tools, manage their own schedules, and deliver results according to project requirements. This role allows for flexibility and the opportunity to work on diverse projects across different industries.

What are some common challenges faced by hourly remote machine learning engineers, and how can they be addressed?

Hourly remote machine learning engineers often encounter challenges such as managing time effectively across multiple projects, ensuring clear communication with distributed teams, and accessing necessary data or computing resources remotely. Building strong routines for regular check-ins and using collaborative tools can help maintain alignment with project goals. Additionally, proactively clarifying expectations and deliverables with clients or team leads can minimize misunderstandings and improve productivity in a remote, hourly environment.

What are the key skills and qualifications needed to thrive as an hourly remote machine learning engineer, and why are they important?

To thrive as an Hourly Remote Machine Learning Engineer, you need strong programming skills (especially in Python), a solid understanding of machine learning algorithms, and experience with data preprocessing, typically supported by a relevant degree or equivalent experience. Familiarity with tools and frameworks such as TensorFlow, PyTorch, scikit-learn, cloud platforms (e.g., AWS, GCP), and version control systems like Git is essential. Excellent time management, self-motivation, and clear communication skills help you collaborate effectively across distributed teams and manage project-based work. These skills and qualities are vital for delivering high-quality results independently, meeting deadlines, and adapting to the dynamic needs of remote projects.

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What job categories do people searching Hourly Remote Machine Learning Engineer jobs in Fairfax, VA look for?

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What cities near Fairfax, VA are hiring for Hourly Remote Machine Learning Engineer jobs?

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Hourly Remote Machine Learning Engineer jobs near you
Infographic showing various Hourly Remote Machine Learning Engineer job openings in Fairfax, VA as of August 2026, with employment types broken down into 1% As Needed, 76% Full Time, 21% Part Time, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $43,527 per year, or $20.9 per hour.

Senior Machine Learning Engineer

Clearview AI, Inc.

Washington, DC • Remote

$107K - $146K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 23 days ago

Job description


Clearview AI is the leading provider of facial recognition technologies to US law enforcement, state, and federal agencies. Our mission is to help our users solve crimes and prevent financial fraud with the responsible use of our facial recognition software. Our company is a high-octane, fast growing startup looking to hire enthusiastic and intelligent team members to join our team. To learn more about us, and our revolutionary facial recognition technology, please visit www.clearview.ai.

Senior Machine Learning Engineer


Position Summary: We are hiring a highly technical individual contributor to push the limits of our computer vision and machine learning capabilities. This is a high-impact, hands-on role for a research-minded engineer who wants to build and ship models, not manage a team. Much of the work involves large-scale visual understanding, extracting structured signals from imagery and reasoning about the real-world context behind a photograph, but we care more about deep ML/CV ability than any one problem area and welcome strong generalists.

Responsibilities:
  • Build, train, evaluate, and deploy computer vision and multimodal models, taking them from early prototype through to production
  • Design systems that infer structured attributes and spatial context from imagery, combining learned models with geometric and heuristic reasoning
  • Train and fine-tune models on large, diverse real-world image datasets, and build the pipelines to curate and label that data at scale
  • Work with vision-language models (VLMs) and build rigorous evaluation frameworks to measure their accuracy on our tasks
  • Develop and benchmark high-performance image retrieval capabilities with embedding models and vector indexing strategies
  • Optimize models for inference latency and throughput using techniques like distillation, quantization, and GPU acceleration
  • Read current research, prototype novel algorithms from academic literature, and turn promising ideas into reliable production code
  • Implement efficient, scalable data pipelines and inference infrastructure
  • Develop high-performance tooling in ML and data engineering
  • Additional duties and responsibilities as reasonably required by the employee's supervisor or CEO
Requirements:
  • Experience building, training, evaluating, and deploying ML models in production
  • Strong experience using PyTorch, JAX, or other deep learning frameworks to develop and optimize models
  • Strong software engineering ability to build and maintain complex systems and work with large-scale datasets
  • Ability to solve open-ended problems and quickly learn new domains
  • Comfort operating with significant ownership and autonomy, making pragmatic trade-offs between model sophistication, velocity, inference and business constraints
  • BS, MS, or PhD in Computer Science or a related technical field, or equivalent practical experience

Nice to have:
  • Experience inferring structured, real-world attributes from images
  • Experience training models on large-scale, real-world image datasets
  • Familiarity with vision-language models (VLMs)
  • Ability to digest academic literature, prototype novel algorithms, and bridge the gap between research and production code
  • Experience building LLM or VLM pipelines and the evaluation frameworks to measure their performance
  • Experience in an ML role at a growth-stage startup
  • Publications in major ML or computer vision conferences (e.g., CVPR, ICML, ICCV, WACV)
  • Medical, Dental, Vision, STD and LTD Plans
  • FSA - Medical and Dependent Care
  • EAP and wellness programs
  • 13 Paid Holidays
  • Unlimited PTO
  • Flexible work environment - 100% remote
  • 401(k) plan

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