Job Title: ML Engineer - Computer Vision
Job Overview:
As a Machine Learning Engineer specializing in computer vision at Drizz, you will develop, deploy, and optimize advanced visual recognition and analysis systems. Your work will power key features in our products, enabling applications such as object detection, image segmentation, and real-time video analytics. Collaborating closely with data scientists, software engineers, and product managers, you will ensure that our vision-driven solutions deliver robust, scalable, and high-performance results.
Key Responsibilities:
Model Development & Optimization:
- Design, develop, and fine-tune machine learning models for computer vision tasks, including object detection, image classification, segmentation, and anomaly detection.
- Experiment with state-of-the-art architectures (e.g., CNNs, Transformers, GANs) to improve model accuracy and efficiency.
- Implement rigorous testing protocols to ensure model reliability and performance in production.
Data Handling & Pipeline Engineering:
- Develop and maintain end-to-end data pipelines for processing large-scale image and video datasets.
- Collaborate with data engineers to optimize data ingestion, storage, and retrieval processes for vision data.
- Ensure data quality and integrity through systematic preprocessing, augmentation, and labeling strategies.
Deployment & Scalability:
- Collaborate with DevOps and software engineering teams to integrate computer vision models into production environments.
- Optimize models for deployment on various platforms, including cloud services and edge devices.
- Monitor model performance in real-world scenarios and implement continuous improvement processes.
Research & Innovation:
- Stay current with the latest trends and breakthroughs in computer vision and machine learning.
- Evaluate and prototype new tools, frameworks, and techniques to keep Drizz at the cutting edge of AI innovation.
- Document research findings and share insights with internal teams to foster a culture of innovation.
Collaboration & Communication:
- Work closely with cross-functional teams to align vision model capabilities with business objectives.
- Clearly document technical approaches, model architecture decisions, and experimental results.
- Mentor junior engineers and contribute to team knowledge-sharing sessions.
Required Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Mathematics, or a related field.
- 3+ years of hands-on experience in machine learning with a focus on computer vision applications.
- Proficiency in Python and deep learning frameworks such as TensorFlow, PyTorch, or similar.
- Solid understanding of computer vision algorithms, neural network architectures, and image processing techniques.
- Experience with large-scale image or video data handling and model deployment strategies.
- Strong analytical and problem-solving skills with a passion for driving innovation.