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Generative 3D Jobs in Washington (NOW HIRING)

Words relevant to Quidient include Generative AI, Physics-Informed AI, Large Scene Models (LSMs ... Stay current with the deep learning and 3D vision literature, applying good judgment about which ...

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 ...

Staff Data Scientist

North Bethesda, MD · On-site

$163K - $190K/yr

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 ...

Software Engineer

Reston, VA · On-site

$57K - $104K/yr

Integrate AI/ML capabilities , including Generative AI and LLM APIs * Collaborate across teams to ... Experience integrating COTS/GOTS tools , including 3D modeling, simulation, or visualization ...

Integrate AI/ML capabilities , including Generative AI and LLM APIs * Collaborate across teams to ... Experience integrating COTS/GOTS tools , including 3D modeling, simulation, or visualization ...

Graphics Software Engineer

College Park, MD · On-site

$138K - $171K/yr

... neural rendering, generative medical visualization, real-time inference, and data-driven ... Hands-on experience building XR prototypes/apps in Unity3D and/or Unreal Engine Familiarity with 3D ...

... 3D sensing, anti-counterfeiting, consumer electronics, industrial, automotive, government and ... Utilization of generative AI tools to assist in concept and implementation of FPGA designs * Strong ...

... 3D sensing, anti-counterfeiting, consumer electronics, industrial, automotive, government and ... Utilization of generative AI tools to assist in concept and implementation of FPGA designs * Strong ...

Showing results 21-40

Generative 3D information

What is the difference between Generative 3D vs 3D Modeler?

AspectGenerative 3D3D Modeler
Primary FocusUsing algorithms and AI to automatically generate 3D contentManually creating detailed 3D models based on specifications
Required SkillsProgramming, AI, procedural modeling3D modeling software, artistic skills
Work EnvironmentTech companies, AI labs, digital content creationDesign studios, gaming, animation
CertificationsComputer science, AI, 3D software proficiency3D modeling software certifications, art degrees

Generative 3D specialists focus on creating 3D content through algorithms and AI, automating parts of the modeling process. In contrast, 3D Modelers manually craft detailed models using software tools. Both roles are essential in digital content creation but differ in approach, skills, and work environment.

What is a generative 3d artist?

A Generative 3D artist is a professional who uses algorithms, code, and artificial intelligence to create three-dimensional visual content. They leverage generative design techniques and tools to produce complex, innovative 3D models, animations, and environments that may be difficult to achieve manually. These artists often work in industries such as gaming, film, architecture, and virtual reality, where procedural content and automation can enhance creativity and efficiency. Their expertise combines traditional 3D modeling skills with programming and a strong understanding of computational design.

What are some common challenges faced by professionals working in generative 3d roles, and how can they be addressed?

Professionals in Generative 3D often encounter challenges such as balancing creative freedom with technical constraints, managing computational resources for complex scenes, and ensuring compatibility across different software and platforms. Staying updated with rapidly evolving tools and algorithms can also be demanding. To address these challenges, it's helpful to engage in continuous learning, collaborate closely with both technical and artistic team members, and participate in industry forums to share solutions and best practices.

What are the key skills and qualifications needed to thrive as a generative 3d designer?

To thrive as a Generative 3D Designer, you need a solid background in 3D modeling, algorithmic or procedural design, and computer graphics, often supported by a degree in design, computer science, or a related field. Familiarity with tools like Blender, Houdini, Autodesk Maya, and programming languages such as Python or C++ is typically required. Creativity, problem-solving, and effective communication are crucial soft skills to excel when working with multidisciplinary teams and interpreting complex design briefs. Mastering these skills ensures the ability to create innovative 3D content efficiently, adapt to evolving technologies, and meet diverse project requirements.
What are popular job titles related to Generative 3D jobs in Washington? For Generative 3D jobs in Washington, the most frequently searched job titles are:
What cities in Washington are hiring for Generative 3D jobs? Cities in Washington with the most Generative 3D job openings:
Infographic showing various Generative 3D job openings in Washington as of June 2026, with employment types broken down into 1% As Needed, 91% Full Time, 3% Part Time, 1% Temporary, and 4% Contract. Highlights an 82% Physical, 4% Hybrid, and 14% Remote job distribution.

Senior Offline Mapping Engineer

Quid, Inc.

Columbia, MD • On-site

$175 - $230/hr

Other

Medical, Life, Retirement

Posted 4 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

Quidient is seeking a Senior Offline Mapping Engineer to own and advance the accuracy and robustness of our offline mapping and 3D reconstruction systems. This role sits at the core of our Generalized Scene Reconstruction Platform, where classical SfM and multi-view stereo provide the foundation and modern deep learning methods push quality over the edge — particularly in textureless, featureless, and highly reflective environments that defeat traditional approaches. You will enhance the pipeline that turns real-world captures into highly accurate, production-quality 3D reconstructions.

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

Offline Mapping & Reconstruction
  • Develop and advance our offline mapping and reconstruction pipeline, driving accuracy and robustness across the hardest capture scenarios — textureless walls, highly reflective surfaces, featureless geometry, and large-scale scenes.
  • Reduce pose estimation failures and increase geometric accuracy in environments where classical methods degrade, using a combination of improved estimation and learned components.
  • Design and integrate deep learning methods (learned feature matching, monocular depth priors, learned outlier rejection) alongside classical SfM and MVS components to close the last 10% of reconstruction quality.
  • Improve calibration pipelines, bundle adjustment robustness, and dense reconstruction fidelity in offline processing contexts where throughput matters but hard real-time does not.
Research Integration & Evaluation
  • Build and maintain evaluation methodology grounded in real-world captures — covering feature-rich, textureless, and reflective environments — not synthetic benchmarks alone.
  • Stay current with the deep learning and 3D vision literature, applying good judgment about which methods are production‑viable and which are benchmark artifacts.
  • Collaborate closely with the SLAM and real‑time mapping team to share components and ensure offline improvements feed back into the broader reconstruction platform.
Must-Have Qualifications
  • Master’s, or PhD in Computer Science, Computer Vision, Robotics, or a related field — or equivalent demonstrated experience. This is a Senior‑to‑Staff level role.
  • Significant hands‑on experience building or substantially improving an offline SfM, multi‑view stereo, or dense reconstruction system in production — not just research prototypes.
  • Strong C++ and Python.
  • Deep working knowledge of multiview geometry, bundle adjustment, nonlinear estimation, and — critically — the practical failure modes of each.
  • Real experience with sensor calibration on real hardware.
  • Hands‑on ability to design, train, and integrate deep learning components (learned matching, depth estimation, feature extraction) into a classical reconstruction pipeline using PyTorch or equivalent.
  • 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.
  • Prior work on reconstruction of textureless, reflective, or geometrically challenging environments.
  • Published or shipped work combining learned and classical methods in 3D vision pipelines.
  • Expertise in neural scene representations (NeRF, Gaussian Splatting, or similar).
  • Experience with large‑scale numerical optimization.
  • Contributor to open‑source SfM, MVS, or 3D reconstruction projects (COLMAP, OpenMVS, or similar).
  • Track record of shipping mapping or reconstruction systems at production scale.
Compensation
  • Salary Range: $175,000 - $230,000
  • Annual bonus and equity as appropriate.
  • Health insurance
  • HSA
  • 401(k) with company match
  • Life & disability insurance
  • 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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