Senior Data Science Manager

Develop Computer Vision Algorithms:

Design, train, and optimize deep learning models for tasks such as object detection, segmentation, image classification, and pose estimation.
Implement and refine image processing techniques for feature extraction, noise reduction, and data augmentation.

Build Scalable Models:

Collaborate with engineering teams to integrate vision models into production systems.
Develop scalable and efficient pipelines for real- time video and image data processing.

Data Analysis and Management:

Leverage techniques like supervised, unsupervised, and self- supervised learning.
Collect, preprocess, and analyze large- scale datasets, including labeled and unlabeled visual data.

Research and Innovation:

Experiment with state- of- the- art architectures like Transformers, GANs, or Diffusion Models to enhance model performance.
Stay updated on the latest advancements in computer vision, deep learning, and AI.

Collaborate Across Teams:

Work closely with cross- functional teams, including data engineers, software developers, and domain experts, to understand business problems and deliver solutions.
Present findings and insights to stakeholders using clear visualizations and reports.

Deploy and Monitor Models:

Monitor model performance and implement strategies for continuous improvement.
Deploy models on cloud platforms or edge devices for real- time applications.

Education:

Bachelor’s or higher degree in Computer Science, Data Science, Artificial Intelligence, or a related field.

Experience:

Proven experience (3- 5+ years) in applying computer vision techniques in real- world projects.
Hands- on experience with large datasets, image processing libraries, and deep learning frameworks.

Technical Skills:

Understanding of algorithm optimization techniques for performance and scalability.
Strong programming skills in Python; proficiency in frameworks like TensorFlow, PyTorch, or OpenCV.
Familiarity with cloud platforms and edge deployment.
Knowledge of MLOps tools and practices for model deployment and monitoring.
Experience with image and video annotation tools.

Soft Skills:

Collaborative mindset and ability to work in interdisciplinary teams.
Effective communication skills to present complex technical findings to non- technical stakeholders.
Strong problem- solving skills with the ability to translate business needs into technical solutions.

Preferred Qualifications

Familiarity with advanced architectures like YOLO, Mask R- CNN, Vision Transformers, or CLIP.
Experience with 3D computer vision, LiDAR data, or point cloud processing.
Knowledge of generative AI models and their applications in computer vision.
Experience with AR/VR applications or simulations.

Cập nhật gần nhất lúc: 2025-08-02 08:20:02