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Neural Rendering Jobs in Baltimore, MD (NOW HIRING)

Quidient

Staff Deep Learning Engineer

Columbia, MD · On-site

$185K - $235K/yr

... 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 ...

Umd

Graphics Software Engineer

College Park, MD

$138K - $171K/yr

This position requires passion for real-time XR programming on cutting-edge hardware while closely integrating AI/ML for neural rendering, generative medical visualization, real-time inference, and ...

Quidient

Future Opportunities

Columbia, MD · On-site +1

AI/ML, Deep Learning, and Neural Rendering * Software Engineering (C++, C#, Python, JavaScript, or full-stack web) * Hardware Integration, Sensors, and Edge Computing * Product, Design, and User ...

Umd

Post-Doctoral Associate

College Park, MD

$48K - $65K/yr

This postdoc will perform research on 3D scene reconstruction, novel view synthesis and inverse rendering, building on state of the art techniques such as neural radiance fields, Gaussian splatting ...

Quidient

Senior Computer Vision Engineer

Columbia, MD · On-site

$160K - $210K/yr

... reconstruction, rendering, and platform services. * Define and maintain interfaces and data ... Experience with 3D reconstruction pipelines, including SfM, MVS, or neural scene representations ...

All JobsNeural Rendering JobsNeural Rendering Jobs in Baltimore, MD

Neural Rendering information

See Baltimore, MD salary details

$13

$20

$35

How much do neural rendering jobs pay per hour?

As of Aug 12, 2026, the average hourly pay for neural rendering in Baltimore, MD is $20.97, according to ZipRecruiter salary data. Most workers in this role earn between $17.45 and $21.01 per hour, depending on experience, location, and employer.

What are some common challenges faced by professionals working in neural rendering, and how can they be addressed?

Professionals in Neural Rendering often encounter challenges related to computational resource demands and the integration of novel algorithms into existing graphics pipelines. Handling large datasets and optimizing neural network architectures for real-time performance can also be complex. Collaboration with cross-functional teams—such as graphics engineers, researchers, and product managers—is essential to ensure solutions are both technically feasible and aligned with project goals. Staying updated with the latest research and leveraging open-source frameworks can help address these challenges effectively.

What is the difference between Neural Rendering vs 3D Graphics Programmer?

AspectNeural Rendering3D Graphics Programmer
Required SkillsMachine learning, neural networks, deep learning frameworksGraphics APIs, shader programming, 3D modeling
Work EnvironmentResearch labs, AI-focused companies, tech startupsGame studios, visual effects companies, simulation firms
Industry UsageEmerging in AI-driven visualization and renderingEstablished in gaming, film, and simulation industries

Neural Rendering focuses on using neural networks and AI techniques to generate or enhance visual content, often requiring expertise in machine learning. In contrast, 3D Graphics Programmers develop traditional graphics algorithms, shaders, and models for real-time rendering. While both roles involve visual content creation, Neural Rendering is more research-oriented and AI-driven, whereas 3D Graphics Programming emphasizes technical implementation within graphics pipelines.

What is neural rendering?

Neural rendering is a cutting-edge technique in computer graphics and artificial intelligence that uses neural networks to generate, manipulate, or enhance images and videos, often producing photorealistic or novel visual content. Unlike traditional rendering methods, which rely heavily on physical modeling and computational geometry, neural rendering leverages deep learning algorithms to synthesize visual data from inputs like 3D models, images, or text descriptions. This technology is used in applications such as virtual reality, gaming, special effects, and creating digital avatars. Neural rendering can significantly reduce the computational cost and time needed for high-quality image synthesis, making it a transformative tool in visual computing industries.

What are the key skills and qualifications needed to thrive as a neural rendering engineer, and why are they important?

To thrive as a Neural Rendering Engineer, you need a strong background in computer graphics, deep learning, and mathematics, generally with a degree in computer science, electrical engineering, or a related field. Experience with frameworks like PyTorch or TensorFlow, GPU programming (CUDA), and familiarity with 3D rendering engines is highly valuable. Strong problem-solving skills, creativity, and effective teamwork set exceptional candidates apart in this role. These competencies are crucial for developing innovative rendering solutions that bridge artificial intelligence and visual computing, enabling breakthroughs in graphics technology.
What are popular job titles related to Neural Rendering jobs in Baltimore, MD? For Neural Rendering jobs in Baltimore, MD, the most frequently searched job titles are:
What job categories do people searching Neural Rendering jobs in Baltimore, MD look for? The top searched job categories for Neural Rendering jobs in Baltimore, MD are:
Neural Rendering jobs near you

Staff Deep Learning Engineer

Quidient

Columbia, MD • On-site

$185K - $235K/yr

Full-time

Medical, Life, Retirement, PTO

Posted 24 days ago

Job description

Quidient is a deep tech AI company pioneering advancements in Generalized (5D) Scene Reconstruction (GSR). GSR is poised to become one of the world's great digital product categories (think GPS, MRI, and LMM). Our flagship GSR product, Quidient Reality®, is a powerful API that enables anyone with a mobile device to virtualize, visualize, and measure anything. Words relevant to Quidient include Generative AI, Physics-Informed AI, Large Scene Models (LSMs), Large World Models (LWMs), and API-First.
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 Do
Research & 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 Bring
Must-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 Offer
Compensation:
  • 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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