Computer Vision Research Engineer

Key Skills

Aartificial intelligence, C++, Computer Vision (CV), GPUs, Large Language Models - LLMs, Machine learning techniques, NumPy, OpenCV, PyTorch, TensorFlow

Job Description

As a member of our dynamic and fast-paced group, you’ll work in different research areas to take new computer vision algorithms/models from prototype to production while coordinating with different teams and stakeholders. In this role you will implement and integrate state-of-the-art deep learning algorithms/models that enable high-quality user experiences for different use cases and applications. All of this while delivering high-quality production code and working with cutting-edge technology.

You must be comfortable working in new computer vision areas, doing research for quickly building competence and bring insights into your work. The ideal candidate will have experience with research in computer vision, expertise with computer vision and deep learning models, machine learning lifecycle management, model training & validation coupled with strong fundamentals and passion in software engineering. Join us navigate the forefront of the computer vision evolution!

Minimum Qualifications

• Experience with Machine Learning (ML), with a particular emphasis on Computer Vision (CV) and Large Language Models (LLMs)
• Published research in the field of Machine Learning, AI or Computer Vision
• Familiarity with research papers, implementing state-of-the-art methods, and adapting them to practical applications
• Ability to develop custom algorithms to solve specific computer vision problems
• Comprehensive knowledge and hands-on experience with fine-tuning approaches and training models
• Experience adapting pre-trained LLMs for downstream tasks
• Experience with TensorFlow, PyTorch or Keras
• Proficiency in Python is essential, especially with libraries such as NumPy, OpenCV, and scikit-image
• Understanding of software development best practices, version control (Git), and CI/CD pipelines.

Preferred Qualifications

• Knowledge of C++ is advantageous for performance optimization and working with low-level vision algorithms
• Skills in optimizing model performance, including model pruning, quantization, and hardware acceleration using GPUs or TPUs
• Strong understanding of image processing techniques such as filtering, edge detection, feature extraction, and transformation
• Experience with object detection, segmentation, and classification algorithms
• Experience working in cross-functional teams