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Scientific Machine Learning Jobs in Washington (NOW HIRING)

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 ...

Samprasoft

Machine Learning Engineer

Mclean, VA

At least a Bachelor's degree in Computer Science, Mathematics, related technical field or equivalent practical experience. * A blend of data engineering, machine learning, and product innovation ...

AI Squared

Machine Learning Engineer

Washington, DC · On-site

Machine Learning Engineer Washington, DC (Hybrid) About the Role: We are seeking a highly skilled ... You will work closely with data scientists, data engineers, and product teams to ensure scalable ...

AI Squared

Machine Learning Engineer

Washington, DC · On-site

Machine Learning Engineer Washington, DC (Hybrid) About the Role: We are seeking a highly skilled ... You will work closely with data scientists, data engineers, and product teams to ensure scalable ...

Ai Squared

Machine Learning Engineer

Washington, DC

Machine Learning Engineer Washington, DC (Hybrid) About the Role: We are seeking a highly skilled ... You will work closely with data scientists, data engineers, and product teams to ensure scalable ...

AI Squared

Machine Learning Engineer

Washington, DC

Machine Learning Engineer Washington, DC (Hybrid) About the Role: We are seeking a highly skilled ... You will work closely with data scientists, data engineers, and product teams to ensure scalable ...

AISquared

Machine Learning Engineer

Washington, DC · On-site

... Machine Learning Engineer to join their core AI team. In this role, you will be responsible for ... scientists and product teams to ensure reliable and efficient solutions. Responsibilities : • ...

Booz Allen Hamilton

Machine Learning Engineer

Mclean, VA

$77K - $176K/yr

You Have: * 2+ years of experience with artificial intelligence, data science, or machine learning engineering, including developing and deploying models * Experience with Python coding and libraries ...

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All JobsScientific Machine Learning JobsScientific Machine Learning Jobs in Washington

Scientific Machine Learning information

Is ML a high paying job?

Scientific Machine Learning roles typically offer high salaries due to the specialized skills required, such as expertise in deep learning, data analysis, and programming with tools like Python and TensorFlow. Compensation varies by industry, experience, and location but generally exceeds average tech salaries for comparable roles.

Which 3 jobs will survive AI?

Scientific Machine Learning professionals will likely continue to be in demand due to their expertise in developing and applying AI models to complex scientific problems. Roles such as data scientists, AI researchers, and machine learning engineers are expected to persist because they require specialized knowledge, critical thinking, and ongoing innovation that AI tools complement rather than replace. These jobs often involve interdisciplinary skills, programming, and understanding of domain-specific data, making them more resilient to automation.

What is scientific machine learning?

Scientific machine learning (SciML) is an interdisciplinary field that combines principles from machine learning and scientific computing to solve complex scientific and engineering problems. It involves developing algorithms and models that can learn from data and physical laws, such as differential equations, to make predictions, optimize systems, or gain insights into phenomena. SciML is widely used in areas like physics, biology, climate science, and engineering, enabling researchers to accelerate simulations and make data-driven discoveries. The field often leverages both traditional numerical methods and modern machine learning techniques, making it a rapidly evolving area of research.

What are some common challenges faced by professionals in Scientific Machine Learning, and how can they be addressed?

Professionals in Scientific Machine Learning often encounter challenges such as integrating domain-specific scientific knowledge with machine learning models, managing large and complex datasets, and ensuring that models are interpretable and physically consistent. Collaboration with domain experts and interdisciplinary teams is essential to bridge knowledge gaps and validate results. To address these challenges, it is helpful to invest time in understanding the underlying scientific principles, keep up-to-date with advancements in both machine learning and scientific fields, and utilize specialized tools and frameworks designed for scientific data.

How much does a machine learning scientist make?

A machine learning scientist typically earns between $90,000 and $150,000 annually, depending on experience, education, and location. Senior roles or those with specialized skills in deep learning or natural language processing can earn higher salaries, often exceeding $180,000.

What are the key skills and qualifications needed to thrive as a Scientific Machine Learning professional, and why are they important?

To thrive as a Scientific Machine Learning professional, you need a strong background in mathematics, statistics, programming (often Python), and domain-specific scientific knowledge, typically with a graduate degree in a STEM field. Proficiency in machine learning frameworks (such as TensorFlow or PyTorch), scientific computing tools (like NumPy, SciPy), and experience with high-performance computing are commonly required. Critical thinking, problem-solving, and collaborative communication are vital soft skills for designing experiments and interpreting complex data. These skills ensure robust, reproducible results and the ability to bridge scientific inquiry with advanced computational methods.

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

AspectScientific Machine LearningData Scientist
Required credentialsAdvanced degrees in CS, ML, or related fields; knowledge of scientific computingDegree in CS, statistics, or related fields; strong analytical skills
Work environmentResearch labs, academia, industry R&D teamsBusiness analytics, tech companies, consulting firms
Industry usageResearch, scientific computing, engineering simulationsBusiness insights, predictive modeling, data analysis

Scientific Machine Learning focuses on integrating scientific knowledge with machine learning techniques for research and engineering applications. Data Scientists analyze data to extract insights and build predictive models for business or operational purposes. While both roles require strong technical skills, Scientific Machine Learning emphasizes scientific computing and domain-specific modeling, whereas Data Scientists focus on data analysis and visualization.

Is 40 too late for data science?

Scientific Machine Learning roles often value skills and experience over age, and many professionals transition into data science or machine learning at various stages of their careers. Learning relevant tools like Python, TensorFlow, or scikit-learn and gaining practical experience can help regardless of age, making 40 not too late to pursue this field.
What are popular job titles related to Scientific Machine Learning jobs in Washington? For Scientific Machine Learning jobs in Washington, the most frequently searched job titles are:
What job categories do people searching Scientific Machine Learning jobs in Washington look for? The top searched job categories for Scientific Machine Learning jobs in Washington are:
What cities in Washington are hiring for Scientific Machine Learning jobs? Cities in Washington with the most Scientific Machine Learning job openings:
Scientific Machine Learning jobs near you
Infographic showing various Scientific Machine Learning job openings in Washington as of June 2026, with employment types broken down into 79% Full Time, and 21% Part Time. Highlights an 88% Physical, 1% Hybrid, and 11% Remote job distribution.
Machine Learning Engineer

Machine Learning Engineer

Cymertek

Chantilly, VA • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 28 days ago

Job description

Machine Learning Engineer
LOCATION
Chantilly, VA 20151
CLEARANCE
TS/SCI Full Poly (Please note this position requires full U.S. Citizenship)
KEY SUMMARY
We are seeking a talented and innovative Machine Learning Engineer to join our team and help build intelligent systems that drive impactful business solutions. In this role, you will work with cutting-edge technologies to design, develop, and deploy machine learning models that solve complex problems and improve decision-making processes. You will collaborate with data scientists, engineers, and product teams to turn data into actionable insights and create scalable models that deliver real-world value. If you are passionate about artificial intelligence, data-driven solutions, and continuously learning in an evolving field, we'd love for you to be part of our team.
*** Please note that our job openings are dynamic and can open or close quickly (much faster than we can publish). If you do not see an opening you are looking for, know that we see almost all types of positons. We strive to keep our listings up to date, but please consider submitting your current resume. Our team will work with you to identify the most recent opportunities that align with your skillset and career goals. We look forward to you joining our family. ***
SIMILAR CAREER TITLES
Data Scientist, AI Engineer, Deep Learning Engineer, Artificial Intelligence Engineer, Research Scientist, Data Engineer, NLP Engineer, Computer Vision Engineer, AI/ML Researcher, Data Analyst, ect.
DEGREE (Level Desired)
Bachelor's Degree
DEGREE (Focus)
Computer Science, Data Science, Artificial Intelligence, Mathematics, Statistics, Software Engineering, Electrical Engineering, Robotics, Computational Biology, Physics, ect.
ALTERNATE EXPERIENCE
General comment on degrees: Most contracts allow additional experience (4-5 years) in lieu of a Bachelor's Degree. Some contracts give 4-5 years experience credit for a Bachelor's Degree. Some contracts give 2 years experience credit for a Master's Degree. We will work with you to find the right fit.
POSITION RESPONSIBILITIES
  • Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning)
  • Ability to design, implement, and optimize machine learning models and workflows
  • Experience working with large, complex datasets
  • Knowledge of data preprocessing and feature engineering
  • Familiarity with cloud-based platforms for machine learning (e.g., AWS, Google Cloud, Azure)
  • Strong problem-solving skills and analytical thinking

REQUIRED SKILLS
  • Proficiency in programming languages (e.g., Python, R, Java)
  • Experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn)
  • Expertise in model evaluation techniques and metrics
  • Strong knowledge of version control tools (e.g., Git)
  • Experience with data visualization tools (e.g., Matplotlib, Seaborn, Tableau)
  • Understanding of database technologies (e.g., SQL, NoSQL)

DESIRED SKILLS
  • Experience with natural language processing (NLP)
  • Knowledge of deep learning techniques (e.g., CNNs, RNNs)
  • Familiarity with deployment tools (e.g., Docker, Kubernetes)
  • Experience with data augmentation and synthetic data generation
  • Ability to collaborate in cross-functional teams (e.g., engineers, product managers)
  • Knowledge of edge computing and model optimization for deployment

PLUG IN to CYMERTEK - And design your future...
YOUR FOREVER CAREER STARTS HERE
Are you looking for more than just a job? Join a company where employees are treated like family, and your career is built to last. We are a growing small business and a trusted federal contractor offering full scope consulting services in information technology, cybersecurity, and analyst workforce development.
At our company, you come first. We're committed to creating an environment where you'll thrive professionally and personally. We provide meaningful, challenging work using cutting-edge technologies while investing in your growth and success. With direct access to company leadership, a laid-back and inclusive atmosphere, and exceptional work-life balance, you'll feel valued every day.
We also believe in taking care of our family - both yours and ours. Our benefits are phenomenal, family-friendly, and designed with your well-being in mind. From employee and family events to career-long support, we create a community you'll never want to leave.
Ready to make your next move the best one? Join us and experience the difference.
BENEFITS
  • Excellent Salaries
  • Flexible Work Schedule
  • Cafeteria Style Benefits
  • 10% - 401k Matching (Vested Immediately)
  • Additional 401k Profit Sharing
  • 30 days Paid Leave/Holiday (No Use or Lose!)
  • The day off for your birthday
  • Medical/Dental/Vision - 100% employee coverage. ($1200 allowance - or a bonus)
  • HSA/FSA
  • AFLAC
  • Long Term/Short Term Disability - 100% employee coverage. No cost to you.
  • Life Insurance - 100% employee coverage. No cost to you.
  • Additional Discretionary Life Insurance
  • Paid Training
  • No long, wordy reviews with tons of paperwork!!!
  • Referral bonus program with recurring annual payments

HOW TO APPLY
Email us at jobs@cymertek.com or apply today: www.cymertek.com
Want to see what our employees think? Click here .
EQUAL OPPORTUNITY EMPLOYER STATEMENT
Cymertek is proud to be an Equal Opportunity Employer committed to fostering an inclusive and diverse workplace. We embrace and celebrate differences in our employees, recognizing that a diverse workforce enhances our creativity, innovation, and overall success. At Cymertek, employment decisions are made based on merit, qualifications, and business needs without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other characteristic protected by applicable laws. We believe in creating an environment where all individuals are treated with respect and dignity, and where opportunities for professional growth and advancement are accessible to everyone, regardless of background or identity.

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