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Deep Learning Engineer Intern Jobs in Maryland (NOW HIRING)

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 ...

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 ...

Software Engineer (Deep Learning)

MD · On-site

$84K - $110K/yr

The Software Engineer will support Barrow Wise and perform the following duties: * Designs and develops scalable solutions using AI and deep learning models * Performs research and testing to develop ...

Machine Learning Engineer

Berlin, MD · On-site

$79.93 - $137.02/hr

We are looking for a skilled Machine Learning Engineer with expertise in perception to strengthen ... Design and implement deep learning models for 3D perception, including object detection, semantic ...

As a Research Scientist Intern at Whiterabbit.ai, you will: * Play a key role in architecting the ... Train on a dedicated high-performance compute cluster specialized for deep learning research * Work ...

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Deep Learning Engineer Intern information

What is the difference between Deep Learning Engineer Intern vs Machine Learning Engineer Intern?

AspectDeep Learning Engineer InternMachine Learning Engineer Intern
Required CredentialsTypically pursuing or holding a degree in Computer Science, Data Science, or related fields; familiarity with deep learning frameworksSimilar educational background; knowledge of machine learning algorithms and programming skills
Work EnvironmentResearch labs, tech companies, startups focusing on neural networks and AI modelsBroader industry settings including finance, healthcare, and tech, working on various ML models
Employer & Industry UsageUsed in companies developing AI products, autonomous systems, and advanced neural network applicationsApplied across industries for predictive analytics, data modeling, and automation tasks

While both roles involve machine learning concepts, a Deep Learning Engineer Intern specializes in neural networks and deep learning frameworks, whereas a Machine Learning Engineer Intern works on a wider range of algorithms and models across various industries.

What are the most commonly searched types of Deep Learning Engineer jobs in Maryland?

The most popular types of Deep Learning Engineer jobs in Maryland are:

What cities in Maryland are hiring for Deep Learning Engineer Intern jobs?

Cities in Maryland with the most Deep Learning Engineer Intern job openings:

Staff Deep Learning Engineer

Quidient

Columbia, MD • On-site

$185K - $235K/yr

Full-time

Medical, Life, Retirement, PTO

Re-posted 7 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.