# Staff Deep Learning Engineer

**Company:** [Quidient](https://hotfix.jobs/companies/quidient)
**Location:** Columbia, MD
**Role:** ML Engineering
**Salary:** $185k – $235k/yr
**Experience:** 6+ years
**Skills:** Deep Learning, neural networks, PyTorch, C++, Python, 3d reconstruction, neural rendering, slam, light transport, CUDA, gpu optimization, Anomaly Detection, Computer Vision
**Posted:** 2026-07-19

> Staff Deep Learning Research Engineer designing and training novel neural network architectures from scratch for Generalized Scene Reconstruction tasks including anomaly detection, neural rendering, and 3D reconstruction. Requires PhD/Master's, 6+ years deep learning research experience, expertise in 3D vision or SLAM, and hybrid work in Columbia, MD.

## Job Description

## Research & Network Design
- Design and train novel deep neural network architectures from scratch for 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.
- 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.
- 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 light transport, 3D reconstruction, or SLAM.
- Drive inference optimization and GPU/CUDA performance work toward real-time and on-device targets.

## Must-Have Qualifications
- Master’s or PhD in Computer Science, Electrical Engineering, Machine Learning, or related field with graduate-level foundation in deep learning theory.
- 6+ years of experience in deep learning research and engineering, with 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.
- Willingness to work on-site in Columbia, MD, in a hybrid capacity.
- Meet security requirements including background check, citizenship verification, and CJIS 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.
- 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.

## Compensation & Benefits
- Salary Range: $185,000 – $235,000.
- Annual bonus and equity.
- Health insurance, HSA, 401(k) with company match, life & disability insurance, paid holidays & generous PTO, opportunities for bonuses, equity, and career growth.

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