The ideal candidate will be responsible for working cross-functionally to understand data and AI needs across multiple business units. To be effective in this position, you must feel comfortable owning the entire computer vision workflow, including leveraging advanced deep learning techniques and state-of-the-art architectures, from data collection and preprocessing to model development, evaluation, and deployment.
Senior Data Scientist
is responsible for developing and delivering elements of engineering solutions to accomplish business goals.
- Develop and optimize computer vision models to enhance image and video understanding.
- Apply
Transfer Learning
techniques to fine-tune pre-trained models for specific tasks. - Implement
Unsupervised Learning
methods for feature extraction and clustering in visual data. - Work with
Vision Transformers
to improve accuracy and scalability in image and video analysis. - Deploy and scale computer vision models and
Machine Learning
on Azure. - Fine-tune and evaluate deep learning models for task-specific reasoning and accuracy.
- Experiment, iterate, and deploy features quickly based on real customer feedback.
- Work with a small but highly skilled team to push the limits of industrial AI.
- Take ownership of challenges, figure things out as you go, and adapt to changing priorities.
[Requirements]
- B.S. with 5 years of industry experience OR M.S. with 3 years of industry experience, OR PhD in Computer Science, Math, or a related field with a focus on Computer Vision/Deep Learning.
- Strong Python development skills, with experience in
Machine Learning
and
Deep Learning
. - Expertise in
Computer Vision
frameworks such as OpenCV, PyTorch, TensorFlow, or Keras. - Experience with
Transfer Learning
techniques to adapt pre-trained models for new tasks.g. - Experience with video analysis techniques, including object tracking, action recognition, and scene understanding.
- Understanding of best practices for image and video preprocessing, augmentation, and feature extraction.
- Experience working with Azure for cloud-based ML deployment.
- Knowledge of video indexing and retrieval techniques for large-scale datasets.
- Ability to work in a fast-paced, experimental environment, where iteration and adaptation are key.
- A strong problem-solver who thrives when thrown in at the deep end.