AI Computer Vision Engineer Jobs

View detail

Developing new computer vision algorithms with founders in C/C++ and Python for solving challenging real-world problems, coming up with large scale data collection techniques for training Deep Neural Nets, driving the development of new algorithms that dramatically improve existing methods, researching and maintaining state-of-the-art ML/CV algorithms that can analyze images, and coding full-stack building products from end to end.

View detail

Design, build, implement and optimize multi-stage computer vision pipelines that span segmentation, object detection, multimodal LLM/LVM extraction, machine-readable code decoding, and multi-source reconciliation. Train or fine-tune detection models on custom medical supply datasets. Build and own dataset strategy including leveraging augmentation and synthetic data generation to improve training and testing datasets when data is scarce. Monitor and improve pipeline accuracy by instrumenting field-level metrics, diagnosing failure modes, and systematically improving precision and recall through model iteration and preprocessing optimization. Design persistence schemas and audit data models to ensure every data extraction is independently reviewable. Maintain and extend asynchronous Python backend services that provide pipeline results to downstream clinical workflows.

View detail

Design and implement algorithms for 3D point cloud processing, object detection, and segmentation. Enhance and optimize SLAM pipelines for real-time mobile and static environments. Work on camera–LiDAR calibration and multi-sensor data alignment. Apply deep learning techniques to 2D, 3D, and spatial data. Integrate and optimize tools such as Open3D and 2D+3D inference models into existing systems. Optimize computer vision models and pipelines for NVIDIA GPUs. Perform profiling and performance optimization to improve latency and accuracy. Collaborate with cross-functional teams across Pakistan and Hong Kong to deliver product features. Participate in R&D to evaluate new computer vision and robotics techniques. Ensure robustness and reliability of computer vision systems in real-world conditions. Support and guide junior engineers through reviews and technical discussions.

View detail

The Computer Vision Engineer will deliver hands-on computer vision work and architect technical solutions for complex project requirements. They will lead the technical delivery of computer vision projects and provide expert guidance to multidisciplinary teams throughout the development lifecycle. The role includes contributing expert computer vision insight to bids and identifying opportunities to integrate advanced visual intelligence into customer solutions. The engineer will stay at the forefront of the field by mastering State-of-the-Art developments and sharing best practices across the business unit. They will represent the organization internally and externally as a subject matter expert in computer vision, partner with leadership to define the technical strategy for computer vision work, take ownership of capability development within the Defence domain, and mentor and develop team members interested in computer vision, fostering a continuous learning and technical excellence environment.

View detail

As a Senior Computer Vision Engineer at 42dot, responsibilities include researching and developing 3D computer vision and machine learning algorithms for autonomous driving technology, performing 3D shape modeling and processing, implementing object pose estimation and tracking algorithms, developing efficient and scalable vision solutions, exploring the intersection of vision and robotics, working on low-level and physics-based vision algorithms, conducting self-supervised representation learning from large-scale unlabeled scene data, and creating world models and closed-loop simulation for autonomous driving.

View detail

Engineer an advanced Generative AI pipeline capable of transforming the context of existing datasets, including shifting time-of-day, changing seasons, or altering biomes and weather systems while preserving small target objects like drones. Take ownership of a multi-pass diffusion pipeline to adapt scene contexts and maximize physical realism. Improve custom masking and high-resolution depth-patching algorithms to anchor small objects in 3D space, eliminating artifacts. Generate large-scale augmented datasets and quantify their impact on downstream model performance, designing experiments to measure the effect of synthetic data on the accuracy, recall, and robustness of object detectors when tested against real-world edge cases.

View detail

Conduct research on state-of-the-art Computer Vision methodologies and participate in creating and curating training and validation datasets. Perform statistical analyses and develop visualization tools to ensure data quality. Build and refine training pipelines and metrics to enhance model performance. Develop and optimize Computer Vision algorithms for multiple robotics/aerospace projects. Implement ML/CV models into production-ready environments, ensuring seamless integration with Harmattan AI’s systems and conducting rigorous code reviews. Test algorithms in real-world environments and develop monitoring tools to track model performance and continuously improve deployed solutions. Work closely with software and simulation teams to align development with system requirements and communicate findings effectively to stakeholders.

View detail

The Computer Vision Engineer is responsible for developing the front-end of the visual inertial odometry (VIO) algorithmic stack, including matching between frames and stereo pairs, calibration of camera intrinsic and extrinsic parameters, and detection of obstruction. They will implement and optimize the algorithmic stack for embedded platforms, conduct testing, validation, and monitoring of algorithms in simulation and real-world environments, and develop inspection and monitoring tools. The role also involves cross-team collaboration, working closely with system engineers, optical engineers, and software engineers, and effectively communicating findings to stakeholders.

View detail

The responsibilities include conducting research on state-of-the-art Computer Vision methodologies and participating in the creation and curation of training and validation datasets. Performing statistical analyses and developing visualization tools to ensure data quality. Building and refining training pipelines and metrics to enhance model performance. Developing and optimizing Computer Vision algorithms for multiple robotics/aerospace projects. Implementing ML/CV models into production-ready environments, ensuring seamless integration with Harmattan AI’s systems, and conducting rigorous code reviews. Testing algorithms in real-world environments, developing monitoring tools, tracking model performance, and continuously improving deployed solutions. Working closely with software and simulation teams to align development with system requirements and communicating findings effectively to stakeholders.

View detail

Lead and manage the acquisition program lifecycle, including due diligence, integration, and adoption to completion across multiple acquisitions. Collaborate with cross-functional stakeholders and establish program management foundations and processes to ensure successful implementations within Anduril.