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Geometric Deep Learning Jobs in Washington (NOW HIRING)

Software Engineer, Applied AI

Washington, DC · On-site

$165K - $250K/yr

... geometric deep learning, large language models (LLM), and generative AI * Ability to operate a Vector Database * Ability to program in TypeScript and Python * Ability to pre-train and fine tune large ...

Senior Director & Product Lead

North Bethesda, MD · Hybrid

$233K - $244K/yr

You can go toe-to-toe with Staff Engineers and Data Scientists on topics like geometric deep learning, native 3D geometry processing, and cloud-to-enterprise security architectures. * "Super IC ...

Software Engineer, Applied AI

Washington, DC · On-site

$165K - $250K/yr

... geometric deep learning, large language models (LLM), and generative AI * Ability to operate a Vector Database * Ability to program in TypeScript and Python * Ability to pre-train and fine tune large ...

Deep expertise in Geometric Deep Learning, Computer Vision (3D mesh/B-Rep processing), or Generative AI is highly preferred given the focus on native 3D geometry. * Strategic Delivery: Proven ability ...

Deep expertise in Geometric Deep Learning, Computer Vision (3D mesh/B-Rep processing), or Generative AI is highly preferred given the focus on native 3D geometry. * Strategic Delivery: Proven ability ...

Senior Director & Product Lead

North Bethesda, MD · On-site

$233K - $244K/yr

You can go toe-to-toe with Staff Engineers and Data Scientists on topics like geometric deep learning, native 3D geometry processing, and cloud-to-enterprise security architectures. * "Super IC ...

Math 1 Tutor

Alexandria, VA · Remote

$40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for ... Deep knowledge of linear equations and inequalities, functions and function families, systems of ...

Math 1 Tutor

Fairfax, VA · Remote

$40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for ... Deep knowledge of linear equations and inequalities, functions and function families, systems of ...

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for ... Deep knowledge of linear equations and inequalities, functions and function families, systems of ...

Math 1 Tutor

Washington, DC · Remote

$40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for ... Deep knowledge of linear equations and inequalities, functions and function families, systems of ...

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Geometric Deep Learning information

What is geometric deep learning?

Geometric deep learning is a field of machine learning that focuses on the design of neural network architectures capable of processing data with non-Euclidean structures, such as graphs, manifolds, and point clouds. Unlike traditional deep learning methods, which work well with grid-like data such as images, geometric deep learning tackles challenges where data has more complex, irregular structures. Applications include social network analysis, 3D shape recognition, drug discovery, and recommendation systems. The field aims to generalize deep learning techniques to data that is best represented by geometric or topological constructs.

What is the difference between Geometric Deep Learning vs Data Scientist?

AspectGeometric Deep LearningData Scientist
Required CredentialsAdvanced degrees in computer science, machine learning, or related fieldsBachelor's or master's in data science, statistics, or related fields
Work EnvironmentResearch labs, AI development teams, academiaBusiness analytics, product teams, consulting firms
Industry UsageAI, robotics, computer vision, graph analysisBusiness intelligence, marketing, finance, healthcare

Geometric Deep Learning focuses on applying deep learning techniques to non-Euclidean data like graphs and manifolds, often requiring advanced technical skills. Data Scientists analyze and interpret data to inform business decisions, typically working with structured data and statistical tools. While both roles involve data analysis, Geometric Deep Learning is more research-oriented and specialized in AI development, whereas Data Scientists focus on practical data insights across industries.

What are some common challenges faced when working on Geometric Deep Learning projects, and how can they be addressed?

One common challenge in Geometric Deep Learning is dealing with the complexity and diversity of data structures, such as graphs, point clouds, or manifolds. These data types often require specialized neural network architectures and custom preprocessing steps, which can be more complex than traditional deep learning tasks. Collaboration with domain experts and staying updated with the latest research are crucial for overcoming these obstacles. Additionally, debugging and visualizing the learning process can be more challenging, so employing robust evaluation metrics and visualization tools is highly recommended.

What are the key skills and qualifications needed to thrive as a Geometric Deep Learning Engineer, and why are they important?

To excel as a Geometric Deep Learning Engineer, you need a strong background in mathematics, machine learning, and computer science, typically supported by an advanced degree in a related field. Proficiency with deep learning frameworks like PyTorch or TensorFlow, as well as experience with graph neural networks (GNNs) and geometric data structures, is essential. Strong analytical thinking, problem-solving abilities, and collaborative communication are key soft skills for innovating and working with interdisciplinary teams. These skills are crucial for developing cutting-edge models that leverage geometric data, enabling impactful solutions across domains such as computer vision, biology, and social network analysis.
What are popular job titles related to Geometric Deep Learning jobs in Washington? For Geometric Deep Learning jobs in Washington, the most frequently searched job titles are:
What job categories do people searching Geometric Deep Learning jobs in Washington look for? The top searched job categories for Geometric Deep Learning jobs in Washington are:
Infographic showing various Geometric Deep Learning job openings in Washington as of June 2026, with employment types broken down into 50% Full Time, and 50% Part Time. Highlights an 25% In-person, 25% Hybrid, and 50% Remote job distribution.
Machine Learning Engineer

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 6 days ago


Job description

Description

Do you have demonstrated machine learning experience and want to apply that experience to solving a wide variety of complex problems in this rapidly evolving field?

Do you thrive in a collaborative research environment, working alongside an energetic, multidisciplinary team of scientists and engineers?

Are you ready to help the US secure and maintain leadership in the development and deployment of AI/ML algorithms for non-kinetic defense systems?

If so, we're looking for someone like you to join our team at APL!

We are seeking an experienced Machine Learning Engineer who will contribute to all phases of the machine learning algorithm development and implementation. You will be joining a team of engineers and scientists who are at the forefront of APL's mission to provide innovative solutions to critical challenges.

As a Machine Learning Engineer, you will...

  • Design, implement, and evaluate advanced machine learning algorithms to solve challenging real-world planning, perception, coordination, and control problems in support of national defense.
  • Develop software pipelines to integrate data streams, simulation environments, and intelligent decision-making algorithms.
  • Work with technologies and concepts at the cutting edge of AI, including but not limited to: deep reinforcement learning, foundation models, large language models, convolutional/recurrent/graph neural networks, computer vision, and physics-based modeling and simulation tools.
  • Collaborate closely with the talented team of scientists and engineers in our group and with others across APL.
  • Engage directly with sponsors to communicate proposed concepts, solutions, and analysis.

Qualifications

You meet the minimum requirements for the job if you...

  • Have a Bachelor's degree in Mathematics, Physics, Engineering, Computer Science, or a related field.
  • Have at least 2+ years of experience in machine learning and data science fields.
  • Have at least one year of hands-on experience applying/developing machine learning algorithms using common libraries such as PyTorch or TensorFlow.
  • Have strong foundational knowledge in at least two of the following: classification, clustering, deep learning, reinforcement learning, computer vision (object detection and visual tracking), multi-agent systems, or optimization/control theory.
  • Have demonstrated experience in working with version control software like Git.
  • Have strong, effective communication skills both verbal and written.
  • Are able to obtain an Interim Secret level security clearance by your start date and can ultimately obtain a Secret level clearance. If selected, you will be subject to a government security clearance investigation and must meet the requirements for access to classified information. Eligibility requirements include U.S. citizenship.

You 'll go above and beyond our minimum requirements if you...

  • Have an MS in Mathematics, Physics, Engineering, Computer Science, or a related field.
  • Have 5+ years of experience in designing and implementing AI/ML algorithms for a variety of datasets.
  • Have proven experience applying state-of-the-art deep learning techniques to solve distributed resource allocation problems.
  • Have hands-on experience building computer vision pipelines for detection, tracking, segmentation, or multi-modal sensor fusion.
  • Have experience with modeling and simulation platforms such as AFSIM, Blender, Unity, or Unreal.
  • Are comfortable working in high performance computing environments (GPU/CPU clusters).
  • Have proficiency in one or more of the following technology areas: multi-agent reinforcement learning, geometric deep learning, multi-modal sensor fusion, agentic AI.
  • Have a track record of writing deployable, production-level code (Python, C/C++) for real-world applications.

#LI-KW1

About Us

Why Work at APL?

The Johns Hopkins University Applied Physics Laboratory (APL) brings world-class expertise to our nation's most critical defense, security, space and science challenges. While we are dedicated to solving complex challenges and pioneering new technologies, what makes us truly outstanding is our culture. We offer a vibrant, welcoming atmosphere where you can bring your authentic self to work, continue to grow, and build strong connections with inspiring teammates.

At APL, we celebrate our differences of perspectives and encourage creativity and bold, new ideas. Our employees enjoy generous benefits, including a robust education assistance program, unparalleled retirement contributions, and a healthy work/life balance. APL's campus is located in the Baltimore-Washington metro area. Learn more about our career opportunities athttp://www.jhuapl.edu/careers.

All qualified applicants will receive consideration for employment without regard to race, creed, color, religion, sex, gender identity or expression, sexual orientation, national origin, age, physical or mental disability, genetic information, veteran status, occupation, marital or familial status, political opinion, personal appearance, or any other characteristic protected by applicable law.APL is committed to providing reasonable accommodation to individuals of all abilities, including those with disabilities. If you require a reasonable accommodation to participate in any part of the hiring process, please contactAccommodations@jhuapl.edu.

The referenced pay range is based on JHU APL's good faith belief at the time of posting. Actual compensation may vary based on factors such as geographic location, work experience, market conditions, education/training and skill level with consideration for internal parity. For salaried employees scheduled to work less than 40 hours per week, annual salary will be prorated based on the number of hours worked. APL may offer bonuses or other forms of compensation per internal policy and/or contractual designation. Additional compensation may be provided in the form of a sign-on bonus, relocation benefits, locality allowance or discretionary payments for exceptional performance. APL provides eligible staff with a comprehensive benefits package including retirement plans, paid time off, medical, dental, vision, life insurance, short-term disability, long-term disability, flexible spending accounts, education assistance, and training and development. Applications are accepted on a rolling basis.

Minimum Rate
$100,000 Annually
Maximum Rate
$245,000 Annually