What are the responsibilities and job description for the Computer Vision Engineer position at Objectways?
About Us:
Objectways Technologies is a leading provider of data annotation, sourcing, and content moderation services with deep expertise in LiDAR, Generative AI, and Large Language Models (LLMs). We specialize in delivering high-quality data to power cutting-edge AI applications across industries like autonomous driving, retail, healthcare, and more. We are looking for a talented **Computer Vision Data Scientist** to join our team and help drive innovative solutions in the rapidly evolving field of computer vision.
Job Description:
As a **Computer Vision Data Scientist**, you will be responsible for developing, deploying, and optimizing state-of-the-art computer vision models to solve real-world challenges. You will work with cross-functional teams, including data engineers, annotation specialists, and product teams, to build scalable solutions that leverage computer vision technologies such as object detection, segmentation, image classification, and 3D vision.
You will play a key role in exploring innovative methods for analyzing and interpreting visual data, including images, videos, LiDAR data, and 3D point clouds. This is an exciting opportunity to contribute to the future of AI, impacting industries from autonomous vehicles to retail and manufacturing.
Key Responsibilities:
- Design, develop, and deploy machine learning models for computer vision tasks such as object detection, image classification, semantic segmentation, and facial recognition.
- Apply deep learning techniques (CNNs, RNNs, GANs, etc.) to improve model performance on visual data.
- Work with 2D/3D data modalities (e.g., images, videos, LiDAR, point clouds) to build robust vision-based models.
- Collaborate with data labeling teams to ensure accurate and consistent annotations, as well as define labeling strategies and guidelines for new projects.
- Optimize and fine-tune models to achieve high accuracy, precision, and efficiency in real-world deployments.
- Conduct research and stay updated on the latest computer vision techniques and advancements, incorporating cutting-edge methods into our projects.
- Analyze large-scale datasets, extract meaningful insights, and prepare data for model training and evaluation.
- Develop scalable pipelines to automate data preprocessing, feature extraction, and model training for computer vision tasks.
- Collaborate with product managers and stakeholders to define project goals and deliverables.
- Troubleshoot and resolve issues in existing models and systems to ensure smooth operation and performance.
Qualifications:
Education:
- Bachelor's or Master’s degree in Computer Science, Data Science, Engineering, or a related field. Ph.D. preferred but not required.
Experience:
- 3 years of hands-on experience in computer vision, deep learning, or related fields.
- Proven track record of building and deploying computer vision models using deep learning frameworks such as TensorFlow, PyTorch, or Keras.
- Experience working with large datasets, image processing techniques, and data augmentation.
- Practical experience with 3D computer vision, including LiDAR or 3D point cloud data, is a strong plus.
Technical Skills:
- Strong proficiency in Python and libraries such as OpenCV, NumPy, and Scikit-learn.
- Experience with deep learning frameworks like TensorFlow, PyTorch, or Keras.
- Familiarity with computer vision algorithms such as CNNs, GANs, and object detection frameworks (YOLO, Faster R-CNN).
- Experience with cloud computing platforms (AWS, Google Cloud, or Azure) for large-scale model training and deployment.
- Familiarity with GPU-based computing and optimization for model training.
- Solid understanding of machine learning concepts such as supervised learning, unsupervised learning, and transfer learning.
Soft Skills:
- Strong analytical and problem-solving skills, with the ability to think critically and innovate.
- Excellent communication skills and the ability to work collaboratively in a team environment.
- Attention to detail and a passion for driving high-quality results.
Preferred Qualifications:
- Experience with LiDAR, radar, or multispectral image processing.
- Prior experience working on autonomous driving, robotics, or medical imaging projects.
- Knowledge of reinforcement learning and its applications in computer vision.
- Experience with generative models (GANs) for image synthesis, data augmentation, or style transfer.
- Experience in designing and implementing annotation guidelines for data labeling tasks.
Benefits:
- Competitive salary and performance-based bonuses.
- Flexible work environment with options for remote or hybrid work.
- Opportunities for career growth and professional development.
- Access to cutting-edge tools and technologies in the AI and computer vision space.
- Health, dental, and vision insurance.
- Generous vacation and PTO.
