We're looking for an experienced AI engineer to work on improving the core pieces of our mapping and localization capabilities. The focus of the Senior Computer Vision & Machine Learning Engineer is to enhance our mapping, localization, and 3D reconstruction capabilities. This role focuses primarily on computer vision techniques but also integrates machine learning methodologies to optimize performance on real-world construction site data. You will be working with the AI team to develop innovative solutions leveraging classical computer vision, probabilistic modeling, computational geometry, and deep learning to provide meaningful insights to our customers
Brief summary of role:
- Design and architect complex, multi-component computer vision and machine learning systems.
- Develop and optimize image localization, SLAM, Structure from Motion (SfM), and 3D reconstruction techniques.
- Implement deep learning models for visual perception, leveraging modern machine learning techniques (LLMs, VLLMs, transformers, multi-modal models, and generative AI).
- Prototype and rigorously test algorithms on real-world construction site data.
- Collaborate with platform engineers to transition research prototypes into production-ready implementations.
- Oversee dataset creation, curation, and annotation to ensure high-quality training and validation data.
- Monitor and improve system performance in production, ensuring robustness and scalability.
- Debug and resolve complex failure edge cases in the production processing pipeline.
- Contribute to defining development processes, best practices, and documentation.
What we are looking for:
- M.S./Ph.D. in related field or equivalent industry experience
- 5+ years of industry experience developing computer vision and machine learning models for image processing
- Strong expertise in camera models, camera calibration, and 3D pose representations and transforms.
- Experience with at least one of the following: SLAM, SfM, 3D reconstruction, photogrammetry, or Visual Inertial Odometry (VIO).
- Experience working with IMU and other sensor data.
- Deep understanding of fundamental CV techniques: feature detection and matching, probabilistic modeling, computational geometry, numerical optimization.
- Proficiency in deep learning frameworks such as PyTorch or TensorFlow.
- Expertise in Python programming and numerical algorithm implementation.
- Experience working with multi-modal models combining images and language.
- Familiarity with 3D visualizations and debug interfaces (OpenGL/PyQt).
- Proficiency in cloud computing platforms (AWS, GCP, or equivalent) and software version control systems (Git).
- Strong problem-solving skills and the ability to work on interdisciplinary challenges at the intersection of computer vision, deep learning, and 3D perception.
- Excellent written and verbal communication skills, with the ability to convey complex technical concepts clearly.
Base Salary: $152,000 to $239,500The “Base Salary: range represents the low and high end of the anticipated salary range for this position across all US locations including but not limited to CA, CO, NY, WA, NV, MD, CT and RI. The determination of this anticipated Base Salary involves the consideration of many factors in making compensation decisions including but not limited to: location of candidate, unique skill sets, experience, training, performance, licensure and certifications, as well as other business and organizational needs.
Our anticipated Base Salary determination is just one component of OpenSpace’s competitive total rewards strategy that also includes equity awards, paid time off, 401(k) retirement account, flexible time off, and paid parental leave. as well as other region-specific health and wellness benefits.If this role isn't what you're looking for, please consider other open positions.
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OpenSpace welcomes employees from varied backgrounds and walks of life, and it’s reflected in our diverse community. OpenSpace is proud to be an equal opportunity employer and is committed to providing equal employment opportunities to all employees and applicants for employment, without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
