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Machine Learning Scientist Jobs in Virginia (NOW HIRING)

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Machine Learning Engineer

Mclean, VA · On-site

This role sits at the intersection of applied machine learning, data science, and production systems, with a focus on building and deploying solutions that leverage machine learning, computer vision ...

Cymertek

Machine Learning Engineer

Chantilly, VA · On-site

Machine Learning Engineer LOCATION Chantilly, VA 20151 CLEARANCE TS/SCI Full Poly (Please note this ... You will collaborate with data scientists, engineers, and product teams to turn data into ...

Unissant

Machine Learning Engineer

Ashburn, VA · On-site

$110 - $170/hr

We are seeking a Machine Learning Engineer to join our team and support our client in Ashburn, VA ... Bachelor's Degree in Computer Science, Data Science, Electrical Engineering, Physics, or a related ...

Cymertek

Machine Learning Engineer

Reston, VA · On-site

Machine Learning Engineer LOCATION Reston, VA 20190 CLEARANCE TS/SCI Full Poly (Please note this ... You will collaborate with data scientists, engineers, and product teams to turn data into ...

Cymertek

Machine Learning Engineer

Tysons, VA · On-site

Machine Learning Engineer LOCATION Tysons, VA 22182 CLEARANCE TS/SCI Full Poly (Please note this ... You will collaborate with data scientists, engineers, and product teams to turn data into ...

UNISSANT

Machine Learning Engineer

Ashburn, VA

We are seeking a Machine Learning Engineer to join our team and support our client in Ashburn, VA ... Bachelor's Degree in Computer Science, Data Science, Electrical Engineering, Physics, or a related ...

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All JobsMachine Learning Scientist JobsMachine Learning Scientist Jobs in Virginia

Machine Learning Scientist information

See Virginia salary details

$76.3K

$138.5K

$194K

How much do machine learning scientist jobs pay per year?

As of Aug 25, 2026, the average yearly pay for machine learning scientist in Virginia is $138,506.00, according to ZipRecruiter salary data. Most workers in this role earn between $120,107.00 and $154,146.00 per year, depending on experience, location, and employer.

What is a machine learning scientist?

A Machine Learning Scientist researches, develops, and applies machine learning models to solve complex problems. They work on designing algorithms, improving model performance, and analyzing large datasets to extract valuable insights. Their role often involves experimenting with new techniques, optimizing existing models, and collaborating with engineers and data scientists to deploy solutions. Machine Learning Scientists typically have expertise in statistics, mathematics, and programming languages like Python. They work in industries such as healthcare, finance, and technology to drive innovation using artificial intelligence.

What does a machine learning scientist do?

A typical day for a Machine Learning Scientist involves collecting and analyzing large datasets, designing and training machine learning models, and evaluating model performance to ensure accuracy and reliability. You'll often collaborate with data engineers, software developers, and domain experts to define project goals, prepare data, and integrate solutions into production systems. Regular team meetings, code reviews, and brainstorming sessions are common, fostering an environment of shared learning and problem-solving. This collaborative structure not only enhances project outcomes but also offers valuable opportunities for continuous professional growth and skill development.

What skills and qualifications are needed to be a machine learning scientist?

To thrive as a Machine Learning Scientist, you need strong skills in mathematics, statistics, programming (typically in Python or R), and a graduate degree in computer science, data science, or a related field. Expertise in machine learning frameworks (such as TensorFlow, PyTorch, or scikit-learn), proficiency with data processing tools, and experience with cloud platforms (like AWS or GCP) are commonly required; certifications in these can be advantageous. Critical thinking, problem-solving, and effective communication are important soft skills for collaborating with cross-functional teams and conveying complex concepts. These abilities enable Machine Learning Scientists to build effective models, deliver actionable insights, and drive innovation within organizations.

Is machine learning a high paying job?

Machine Learning Scientists typically earn high salaries due to the specialized skills required, such as programming, statistical analysis, and experience with tools like Python and TensorFlow. Salaries vary by industry, experience, and location but are generally above average compared to many other tech roles.

What are the most commonly searched types of Machine Learning Scientist jobs in Virginia?

The most popular types of Machine Learning Scientist jobs in Virginia are:

What are popular job titles related to Machine Learning Scientist jobs in Virginia?

For Machine Learning Scientist jobs in Virginia, the most frequently searched job titles are:

What job categories do people searching Machine Learning Scientist jobs in Virginia look for?

The top searched job categories for Machine Learning Scientist jobs in Virginia are:

Machine Learning Scientist jobs near you
Infographic showing various Machine Learning Scientist job openings in Virginia as of August 2026, with employment types broken down into 57% Full Time, and 43% Contract. Highlights an 100% In-person job distribution, with an average salary of $138,506 per year, or $66.6 per hour.

AI Research Scientist - Machine Learning

AIToolboard

Richmond, VA • On-site

$120 - $190/hr

Other

Posted 7 days ago

Job description

Jobs / AI Research Scientist - Machine Learning

AI Research Scientist - Machine Learning

Full-time

About the Role

Our client is seeking a brilliant and innovative AI Research Scientist specializing in Machine Learning to join their cutting-edge R&D team in Richmond, Virginia, US. This role is at the forefront of developing next-generation AI technologies and algorithms. You will be responsible for designing, implementing, and evaluating advanced machine learning models, conducting groundbreaking research, andcontributing to high-impact AI applications. The ideal candidate possesses a strong academic background, a deep understanding of ML principles, and a passion for pushing the boundaries of artificial intelligence.Key Responsibilities:Conduct advanced research in machine learning, deep learning, and related AI fields. Design, develop, and implement novel algorithms and models for complex AI problems. Experiment with various ML techniques, including supervised, unsupervised, reinforcement learning, and neural networks. Analyze large datasets, preprocess data, and extract meaningful features for model training. Evaluate model performance, identify areas for improvement, and iterate on designs. Collaborate with software engineers to deploy and integrate AI models into production systems. Stay current with the latest advancements in AI and ML research through literature review and conference participation. Publish research findings in leading scientific journals and present at conferences. Mentor junior researchers and interns, fostering a collaborative research environment. Contribute to the intellectual property portfolio through patent applications.Qualifications:Ph.D. or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Statistics, or a related quantitative field. Proven research experience demonstrated through publications in top-tier AI/ML conferences and journals (e.g., NeurIPS, ICML, ICLR, CVPR). Strong theoretical foundation in machine learning, deep learning, and statistical modeling. Proficiency in programming languages such as Python, and experience with ML libraries like TensorFlow, PyTorch, scikit-learn. Experience with data manipulation and analysis tools. Ability to design and conduct rigorous experiments, interpret results, and draw insightful conclusions. Excellent problem-solving skills and creativity in developing novel solutions. Strong communication and presentation skills, with the ability to articulate complex technical concepts. Experience with distributed computing frameworks (e.g., Spark) is a plus. Experience in specific domains like NLP, computer vision, or reinforcement learning is highly desirable. Join a forward-thinking team that is shaping the future of AI. This exciting opportunity is based in Richmond, Virginia, US .

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