ZipRecruiter

Log In

2

Remote Machine Learning Jobs in Manassas, VA (NOW HIRING)

Elder Research

Data Scientist (Remote)

Arlington, VA · On-site +1

Maintain current in emerging tools and techniques in machine learning, statistical modeling, and ... Washington DC Metro Area - Remote (candidates MUST BE located in the National Capital Region - DMV ...

Elder Research

Data Scientist (Remote)

Arlington, VA · On-site +1

Maintain current in emerging tools and techniques in machine learning, statistical modeling, and ... Washington DC Metro Area - Remote (candidates MUST BE located in the National Capital Region - DMV ...

previous pagenext page

Showing results 21-40

All JobsMachine Learning JobsRemote Machine Learning JobsRemote Machine Learning Jobs in Manassas, VA

Remote Machine Learning information

See Manassas, VA salary details

$25.5K

$42.6K

$88K

How much do remote machine learning jobs pay per year?

As of Aug 6, 2026, the average yearly pay for remote machine learning in Manassas, VA is $42,574.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $46,000.00 per year, depending on experience, location, and employer.

What is a remote machine learning job?

A remote machine learning job involves working with algorithms, data, and models to develop predictive systems or automate tasks, all while working from a location outside of a traditional office setting. Professionals in this role use techniques from statistics and computer science to analyze data, train machine learning models, and deploy solutions for real-world applications. Remote machine learning jobs can span various industries, including technology, healthcare, finance, and e-commerce. These roles typically require strong programming skills, knowledge of machine learning frameworks, and the ability to communicate findings effectively with team members or stakeholders. Working remotely offers flexibility, but also requires discipline and self-motivation to succeed.

What are some effective strategies for collaborating with team members while working remotely as a machine learning engineer?

Collaboration in a remote Machine Learning role often relies on clear communication through digital tools such as Slack, Zoom, and project management platforms like Jira or Asana. Regular check-ins and stand-up meetings help keep everyone aligned on project goals and timelines. Sharing code and models via version control systems (like Git) and using collaborative notebooks (such as JupyterHub or Google Colab) are also common practices. Building strong documentation habits and proactively seeking feedback can help ensure smooth teamwork and project success, even across different time zones.

What is the difference between Remote Machine Learning vs Data Scientist?

AspectRemote Machine LearningData Scientist
Required CredentialsBachelor's/Master's in CS, ML certificationsBachelor's/Master's in CS, Statistics, or related field
Work EnvironmentRemote, collaborative teams, tech companiesRemote or on-site, diverse industries, analytics focus
Industry UsageTech, AI startups, researchFinance, healthcare, e-commerce, tech
Search & Comparison IntentOften compared for technical roles in AI/MLBroader data analysis roles, but overlapping skills

Remote Machine Learning specialists focus on developing algorithms and models primarily in tech environments, often requiring advanced programming and ML knowledge. Data Scientists analyze data to extract insights, sometimes utilizing ML techniques. While both roles share skills and credentials, Remote Machine Learning emphasizes model development, whereas Data Scientists focus on data analysis and interpretation.

Can remote machine learning engineers work remotely?

Yes, remote machine learning engineers can work remotely, as many companies offer flexible work arrangements for data science and AI roles. These positions typically require strong programming skills, experience with tools like Python and TensorFlow, and the ability to collaborate virtually using communication platforms. Remote work in this field is common, especially for roles focused on model development, data analysis, and deployment.
More about Remote Machine Learning jobs
What are the most commonly searched types of Machine Learning jobs in Manassas, VA? The most popular types of Machine Learning jobs in Manassas, VA are:
What job categories do people searching Remote Machine Learning jobs in Manassas, VA look for? The top searched job categories for Remote Machine Learning jobs in Manassas, VA are:
What cities near Manassas, VA are hiring for Remote Machine Learning jobs? Cities near Manassas, VA with the most Remote Machine Learning job openings:
Remote Machine Learning jobs near you
Infographic showing various Remote Machine Learning job openings in Manassas, VA as of August 2026, with employment types broken down into 67% Full Time, and 33% Contract. Highlights an 100% Remote job distribution, with an average salary of $42,574 per year, or $20.5 per hour.

Senior Machine Learning Engineer

Clearview AI, Inc.

Washington, DC • Remote

$118K - $162K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 10 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

Apply