onsite
Computer Vision Engineer
Computer Vision Engineer
The Computer Vision Engineer will assist in building, testing, and integrating CV models for detection, tracking, and classification tasks, as well as working with foundation and VLM models. This role involves data preparation, scripting, evaluation, error analysis, and collaboration on scalable inference pipelines, utilizing a strong foundation in Python and deep learning frameworks.
About the role
About the Role
We are seeking an enthusiastic Computer Vision Engineer to join our team. This role is ideal for individuals eager to build a career in computer vision and AI for real-world automation, contributing to the development and deployment of cutting-edge CV models.
Responsibilities
- Assist in building and testing CV models for detection, tracking, classification tasks, and the latest foundation and VLM models.
- Prepare and annotate image/video datasets, supporting data ingestion and cleaning pipelines.
- Contribute to writing and debugging training scripts, model loaders, and preprocessing functions.
- Run evaluation jobs and generate performance reports using tools like TensorBoard or custom scripts.
- Support error analysis by identifying model weaknesses across edge cases.
- Collaborate with senior engineers on integrating models into scalable inference pipelines.
- Help visualize model outputs, draw bounding boxes, heatmaps, or segmentation masks for explainability.
- Document experiments and code for reproducibility and knowledge sharing.
- Utilize OpenCV, MediaPipe, and scikit-image for preprocessing, motion analysis, and visual overlays.
- Integrate DL models with post-processing logic (e.g., NMS, temporal smoothing, event triggering).
- Ensure low-latency inference by profiling and tuning frame-wise preprocessing.
- Support integration of RTSP video feeds and video decoders in test pipelines.
- Engage in point-cloud ingestion and processing (Open3D/PCL), calibration/registration (ICP/FGR), 3D detection/segmentation with sparse CNNs/PointNet, and RGB–LiDAR–IMU fusion.
Requirements
- Bachelor’s degree in Computer Science, Data Science, or a related technical field.
- 1–3 years of experience or strong internship/projects in computer vision or ML model development.
- Good Python skills and working knowledge of PyTorch or TensorFlow.
- Familiarity with image processing libraries (e.g., OpenCV, PIL) and dataset tools (e.g., COCO format, YOLO datasets).
- Exposure to object detection/tracking projects (academic, hackathons, or prior work).
- Basic understanding of synthetic data or 3D asset usage in training pipelines.
- Familiarity with Git, Linux command line, and Jupyter Notebooks.
- Eagerness to learn, take feedback, and contribute in collaborative development environments.