Data Scientist (Computer Vision & Image Processing)
As a computer vision and deep learning data scientist you will:
- Research, design, implement, and deploy full-stack scalable computer vision, deep learning, and machine learning solutions to novel and R&D problems.
- Keep up with state-of-the-art methods in computer vision and deep learning and apply them to improve and create new solutions.
- Develop and implement state-of-the-art computer vision algorithms for object detection, classification, segmentation, or recognition.
- Collaborate with team members on developing computer vision systems starting from prototype to production.
- Integrating cutting edge machine learning / deep learning techniques with mobile applications.
- You enjoy creative and structured problem solving. You like the challenge of working on complex challenges with structured and unstructured data and are capable of breaking a larger problem into sizable chunks to work on.
- Translate business requirements into quick prototypes or proof of concepts and work with customers directly to uncover operational objectives.
- Bachelor degree in CS or related field.
- PhD or MS in science, engineering, math, statistics or related fields a plus.
- Strong foundation and/or courses taken in programming (3+ yrs in Python, Java, Scala, R, or combined).
- Computer vision related experience and/or courses, image processing, image classification, semantic segmentation, CNN, RNN, etc.
- Experience with machine learning / deep learning tools or frameworks like Scikit learn, XGBoost, Spark, Tensorflow, Keras, or PyTorch.
- Experience in integrating machine learning with Mobile applications is a must. Experience with integrating machine learning / deep learning techniques with iOS and Android app platforms natively.
- Experience with Augmented Reality for mobile apps
- Experience with Swift for iOS development is highly preferable.
- Experience with Django, Flask frameworks a plus.
- Experience with machine learning / deep learning integration with React Native a plus.
- Excellent written and verbal communication skills and ability to communicate effectively to both technical and non-technical audiences.
- Technical fluency; comfortable understanding and discussing architectural concepts and algorithms, assessing tradeoffs and new opportunities with technical team members.
- Experience applying latest advances in deep learning and computer vision research to real-world problems.
- Experience with integrating machine learning / deep learning techniques in mobile applications.
- Experience with cloud computing environments (AWS, Azure, Google cloud).
- Experience in large-scale geospatial querying and analytics on distributed computing systems.
- Professional experience working in engineering teams, and with tools like Git, Jira, SQL.
- Proficient with a distributed computing platform (Hadoop, Spark, etc.).
March 4, 2022
Client Facing (TOEFL 610+)
Anywhere in Mexico
Years of Experience: