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Weekday Machine Learning Research Scientist Jobs in Virginia

STR

Senior Machine Learning Engineer

Arlington, VA

$155K - $195K/yr

... Data Science, Statistics, Mathematics, Physics, or a related technical field * 6+ years of professional software engineering and/or machine learning research experience (or equivalent experience ...

Skyline Scientific Inc

Software Engineer, Senior

Mclean, VA · On-site

$124K - $163K/yr

You also do not need to be a machine learning research scientist. You do need to be a strong coder, a clear thinker, and someone who is excited to work with scientists and engineers to build software ...

STR

Senior Machine Learning Engineer

Arlington, VA · On-site

$155K - $195K/yr

... Data Science, Statistics, Mathematics, Physics, or a related technical field * 6+ years of professional software engineering and/or machine learning research experience (or equivalent experience ...

STR

Senior Machine Learning Engineer

Arlington, VA · On-site

$155K - $195K/yr

... Data Science, Statistics, Mathematics, Physics, or a related technical field * 6+ years of professional software engineering and/or machine learning research experience (or equivalent experience ...

TwinThread

Machine Learning Engineer

Charlottesville, VA · On-site

$90 - $120/hr

Understanding of relational databases * 3+ years of experience as a data scientist, machine ... Generous pay * Cutting edge research opportunities * Competitive medical benefits * Flexible ...

Kitware

Machine Learning Engineer

Arlington, VA · Hybrid

$110K - $160K/yr

Machine learning experience using visual data * Understanding of a variety of machine learning ... Kitware is a research and development software solutions provider with a mission to advance science ...

Kitware

Machine Learning Engineer

Arlington, VA · Hybrid

$110K - $160K/yr

Machine learning experience using visual data * Understanding of a variety of machine learning ... Kitware is a research and development software solutions provider with a mission to advance science ...

Kitware

Machine Learning Engineer

Arlington, VA · On-site

$110K - $160K/yr

Machine learning experience using visual data * Understanding of a variety of machine learning ... Kitware is a research and development software solutions provider with a mission to advance science ...

Elder Research

Machine Learning Engineer

Chantilly, VA · On-site

Machine Learning Engineer General Information Requisition #728 Locations USA-VA-Chantilly Posting ... Support program with R&D and customer-facing goals, to speed the transition of novel applied ...

Elder Research

Machine Learning Engineer

Chantilly, VA · On-site

Machine Learning Engineer General Information Requisition #728 Locations USA-VA-Chantilly Posting ... Support program with R&D and customer-facing goals, to speed the transition of novel applied ...

Saic

Machine Learning Engineer

Chantilly, VA · On-site

$200 - $240/hr

Research and evaluate open-source ML models, fine-tuning them to meet specific operational needs ... Leverage data science techniques to evaluate datasets, identify trends, and inform decision-making ...

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All JobsWeekday Machine Learning Research Scientist JobsWeekday Machine Learning Research Scientist Jobs in Virginia

Weekday Machine Learning Research Scientist information

What are the key skills and qualifications needed to thrive as a Weekday Machine Learning Research Scientist, and why are they important?

To thrive as a Weekday Machine Learning Research Scientist, you need a solid background in mathematics, statistics, programming (Python, R), and a relevant advanced degree such as a Master's or Ph.D. in computer science or a related field. Expertise with machine learning frameworks (like TensorFlow, PyTorch), data processing tools, and familiarity with cloud computing platforms are typically required. Strong analytical thinking, problem-solving abilities, and clear communication skills help you collaborate with teams and present complex findings effectively. These skills are crucial for developing innovative models, delivering impactful research, and ensuring successful implementation in real-world applications.

What does a Weekday Machine Learning Research Scientist do?

A Weekday Machine Learning Research Scientist conducts research and develops new algorithms or models in the field of machine learning, typically during standard business days (Monday to Friday). Their work involves designing experiments, analyzing data, publishing findings, and collaborating with other scientists or engineers. They may focus on improving existing machine learning techniques or creating innovative solutions for real-world problems. This role often requires a strong background in mathematics, computer science, and statistics, as well as proficiency in programming languages like Python or R.

What are some common challenges faced by a Weekday Machine Learning Research Scientist, and how are they typically addressed within the team?

Weekday Machine Learning Research Scientists often encounter challenges such as managing large datasets, tuning complex models, and keeping up with rapidly evolving research. Collaboration is key—team members regularly hold meetings to share findings, brainstorm solutions, and review code. Access to robust computational resources and mentorship from senior researchers helps address technical obstacles, while a structured, weekday schedule allows for focused research and effective work-life balance.

What is the difference between Weekday Machine Learning Research Scientist vs Weekend Machine Learning Research Scientist?

AspectWeekday Machine Learning Research ScientistWeekend Machine Learning Research Scientist
CredentialsMaster's or PhD in Computer Science, Data Science, or related fieldsSame as weekday role
Work EnvironmentTypically in office or research labs during standard hoursFlexible hours, often part-time or project-based
Employer & Industry UsageTech companies, research institutions, startupsFreelance projects, consulting firms, academic collaborations

The main difference between a Weekday Machine Learning Research Scientist and a Weekend Machine Learning Research Scientist lies in their work schedule and environment. Weekday roles usually involve full-time employment with structured hours, while weekend roles are often part-time or freelance, offering more flexibility. Both roles require similar credentials and are used across tech and research industries.

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

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

Weekday Machine Learning Research Scientist jobs near you

Senior Data Scientist / Machine Learning Engineer

Waypoint Human Capital

Tysons, VA • On-site

Full-time

Posted 17 days ago

Job description

Position Title: Senior Data Scientist / Machine Learning Engineer
Position Type: Full-Time, On-Site
Position Location: Tysons, VA
Clearance Required: Active TS/SCI with CI Polygraph or Full Scope Polygraph
Waypoint's client is seeking a dynamic Senior Data Scientist / Machine Learning Engineer with an active TS/SCI CI Poly or higher to join their team. The Senior Data Scientist / Machine Learning Engineer will work directly with data scientists, software engineers, and subject matter experts in the definition of new analytics capabilities able to provide federal customers with the information they need to make proper decisions and enable their digital transformation.
This position works directly with data scientists, software engineers, and subject matter experts to research, design, and deploy machine learning algorithms that support federal customers in digital transformation and data-driven decision making. They will contribute to new analytics capabilities and assist customers in building their own applications. This position requires a bachelor's degree in Computer Science, Electrical Engineering, Statistics, or a related field, 5 to 10 years of relevant experience, and strong Python and applied ML skills. An active TS/SCI with CI Polygraph or Full Scope Polygraph is required.
Responsibilities
The responsibilities include, but are not limited to:
  • Research, design, implement, and deploy Machine Learning algorithms for enterprise applications.
  • Assist and enable federal customers to build their own applications.
  • Contribute to the design and implementation of new features.

Required
  • Active Top Secret clearance with CI Polygraph or Full Scope Polygraph.
  • Bachelor's degree in Computer Science, Electrical Engineering, Statistics, or equivalent fields required.
  • MS or PhD in Computer Science, Electrical Engineering, Statistics, or equivalent fields preferred.
  • Minimum 5-10 years relevant work experience preferred.
  • Excellent programming skills in Python.
  • Applied Machine Learning experience (regression and classification, supervised, and unsupervised learning).
  • Strong mathematical background (linear algebra, calculus, probability, and statistics).
  • Experience with scalable Machine Learning (MapReduce, streaming).
  • Ability to drive a project and work both independently and in a team.
  • Smart, motivated, can-do attitude, and seeks to make a difference.
  • Excellent verbal and written communication skills.
  • Passion for developing team-oriented solutions to complex engineering problems.
  • Thrive in an autonomous, empowering, and exciting environment.
  • Ability to collaborate across multiple functional teams to improve scalability.
  • Ability to convey highly technical concepts and information in written form to both technical and non-technical audiences.
  • Ability to work on multiple concurrent projects.
  • Strong self-motivation and the ability to work with minimal supervision.
  • Team-oriented, energetic, results- and delivery-focused, with a strong commitment to quality and meeting deadlines.
  • Ability to work in an Agile environment.

Desired
  • Hands-on experience deploying and operating applications using IaaS and PaaS on major cloud providers, including Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform (GCP).
  • Proficient in leveraging modern LLM tools to accelerate development workflows and enhance code quality.
  • Experience with deep learning.
  • Experience with natural language processing (NLP).
  • Experience with computer vision.
  • Experience with reinforcement learning.

Apply