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Volunteering Deep Learning Research Jobs in Washington

Quidient

Staff Deep Learning Engineer

Columbia, MD

$185K - $235K/yr

Overview We are seeking a Staff Deep Learning Research Engineer to design, build, and train novel neural network architectures that solve hard problems across Quidient's GSR platform. This is not an ...

Quidient

Staff Deep Learning Engineer

Columbia, MD · On-site

$185K - $235K/yr

Overview We are seeking a Staff Deep Learning Research Engineer to design, build, and train novel neural network architectures that solve hard problems across Quidient's GSR platform. This is not an ...

Barrow Wise Consulting

Software Engineer (Deep Learning)

MD · On-site

$84K - $110K/yr

Performs research and testing to develop deep learning algorithms and predictive models * Develops algorithms such as Bayesian, coordinate descent, gradient descent, and evolutionary * Utilizes big ...

AIToolboard

AI Research Scientist

Washington, DC · On-site

$120 - $180/hr

Conduct original research in areas such as machine learning, deep learning, natural language processing, computer vision, or reinforcement learning. Design, implement, and evaluate novel AI ...

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Volunteering Deep Learning Research information

What is volunteering deep learning research?

Volunteering deep learning research involves contributing your time and skills to support research projects focused on deep learning, often within academic, nonprofit, or open-source communities. Volunteers may help with tasks such as data annotation, coding, literature reviews, or running experiments. This work can be a great way to gain hands-on experience, collaborate with experienced researchers, and make a positive impact without a formal employment relationship. Opportunities are available for individuals with varying levels of expertise, from students to professionals.

What types of projects and tasks can I expect to work on as a volunteer in deep learning research?

As a volunteer in deep learning research, you may be involved in a variety of tasks such as data preprocessing, literature reviews, implementing and testing machine learning models, or assisting with experiments. Depending on the research lab or team, you could also contribute to writing code, analyzing results, or preparing research papers and presentations. Collaboration is common, so you'll likely work closely with researchers, graduate students, and other volunteers. This role is an excellent opportunity to gain hands-on experience, deepen your understanding of deep learning concepts, and build a network within the AI research community.

What are the key skills and qualifications needed to thrive as a volunteering deep learning researcher, and why are they important?

To thrive as a Volunteering Deep Learning Researcher, you need a strong background in mathematics, programming (especially Python), and foundational knowledge of machine learning concepts, often supported by relevant coursework or self-study. Familiarity with deep learning frameworks such as TensorFlow or PyTorch and version control systems like Git is typically required. Curiosity, collaboration, effective communication, and self-motivation are standout soft skills in this role. These skills and qualities are crucial for contributing meaningfully to research projects, learning independently, and advancing innovative solutions within a team-oriented research environment.

What is the difference between Volunteering Deep Learning Research vs Data Scientist?

AspectVolunteering Deep Learning ResearchData Scientist
CredentialsTypically requires knowledge of deep learning frameworks, programming skills, and research experience; often no formal certification neededRequires degrees in data science, statistics, or related fields; certifications like Certified Data Scientist are common
Work EnvironmentResearch-focused, often nonprofit or academic settings, with flexible hoursCorporate or industry settings, structured work hours, project-driven
Employer & IndustryAcademic institutions, research labs, nonprofitsTech companies, finance, healthcare, and other industries

While both roles involve working with data and machine learning, volunteering deep learning research focuses on academic or nonprofit research projects often without formal compensation, whereas data scientists work in industry settings with a focus on applying data analysis to business problems.

What are popular job titles related to Volunteering Deep Learning Research jobs in Washington?

For Volunteering Deep Learning Research jobs in Washington, the most frequently searched job titles are:

What job categories do people searching Volunteering Deep Learning Research jobs in Washington look for?

The top searched job categories for Volunteering Deep Learning Research jobs in Washington are:

What cities in Washington are hiring for Volunteering Deep Learning Research jobs?

Cities in Washington with the most Volunteering Deep Learning Research job openings:

Volunteering Deep Learning Research jobs near you

Staff Deep Learning Engineer

Quidient

Columbia, MD

$185K - $235K/yr

Full-time

Medical, Life, Retirement, PTO

Re-posted 4 days ago

Job description

Overview

We are seeking a Staff Deep Learning Research Engineer to design, build, and train novel neural network architectures that solve hard problems across Quidient's GSR platform. This is not an applied-ML role - you will work from foundational principles to create new networks from scratch, implement cutting-edge papers, and run end-to-end experiments across domains including geometric anomaly detection, neural rendering, and 3D reconstruction quality.

This is a hybrid position, meaning that you will need to live within easy driving distance to our Technology Center in Columbia, Maryland.

What You'll DoResearch & Network Design
  • Design and train novel deep neural network architectures from scratch for a variety of reconstruction tasks - including surface anomaly detection (e.g., dent detection), geometry-based defect identification, and neural rendering improvements.
  • Implement state-of-the-art papers and adapt published architectures to Quidient's specific reconstruction challenges, exercising deep judgment about what will translate from benchmark to production.
  • Identify technical gaps in the current reconstruction pipeline, propose neural network-based solutions, and build the roadmap for how deep learning capabilities evolve across the platform.
  • Design and maintain rigorous evaluation pipelines grounded in real-world captures to measure model performance, regression, and generalization.
Model Development
  • Run end-to-end experiments independently - from hypothesis through data preparation, training, evaluation, and iteration - with minimal supervision.
  • Stay current with the latest advances in deep neural network architectures, training techniques, and optimization methods, continuously bringing relevant ideas into the pipeline.
  • Contribute production-quality C++ and Python to integrate trained models into the reconstruction engine.
  • Bridge deep learning methods with the geometric and physical foundations of the reconstruction platform, applying domain expertise in one or more of: light transport, 3D reconstruction, or SLAM
  • Drive inference optimization and GPU/CUDA performance work toward real-time and on-device targets.
What You BringMust-Have Qualifications:
  • Master's or PhD in Computer Science, Electrical Engineering, Machine Learning, or a related field. A graduate-level foundation in deep learning theory is required, not just applied experience.
  • 6+ years of experience in deep learning research and engineering, with demonstrated ability to design, train, and evaluate novel neural network architectures from scratch.
  • Deep domain expertise in at least one of: light transport, deep learning for 3D vision, or SLAM.
  • Ability to read, critically evaluate, and implement current deep learning papers (CVPR, NeurIPS, ICLR, ICML) and translate them into working systems.
  • Strong software engineering in C++ and Python, with deep proficiency in PyTorch or equivalent frameworks for model development and training.
  • Willingness to work on-site in Columbia, MD, in a hybrid capacity.
  • Meet Quidient, customer, and government security requirements, which may include, but are not limited to a background check, citizenship verification, and Criminal Justice Information Services verification
Nice-to-Have Qualifications:
  • Experience in fast-paced or startup environments.
  • Publications or open-source contributions in deep learning, neural rendering, 3D reconstruction, or computer vision (CVPR, NeurIPS, ICLR, ICML, SIGGRAPH, or similar).
  • Experience designing evaluation pipelines and experiment infrastructure for deep learning research.
  • Hands on with geometric or physics-informed neural networks, or anomaly detection in 3D data.
  • Track record of taking a research idea from paper to production-deployed model.
What We OfferCompensation:
  • Salary Range: $185,000 - $235,000.
  • Annual bonus and equity as appropriate.
Benefits:
  • Health insurance
  • HSA
  • 401(k) with company match
  • Life & disability insurance
  • Paid holidays & generous PTO
  • Opportunities for bonuses, equity, and career growth
Equal Opportunity Employer Statement

Quidient is an Equal Opportunity Employer. Quidient will consider all qualified applicants without regard to race, color, religion, creed, sex, sexual orientation, gender identity, marital status, national origin, age, veteran status, disability, or any other classification protected by applicable state, federal, or local laws.

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