Research, design and implement Deep Learning models.
Understand user requirements and deploy deep learning solutions to solve complex business problems.
Continuously improve performance, efficiency and scalability of existing models and algorithms.
Establish efficient and automated processes for large scale data analysis of unstructured data.
Implement MLOps processes for continuous improvement in the model lifecycle.
Support development of monitoring and re-training procedures for models in production.
Write production code in Python.
Utilize Azure technologies to build efficient and reusable machine learning pipelines. Stay up to date with the latest advancements in data science techniques.
Work closely with an international team of Data Scientists, Machine Learning and Software Engineers.
Minimum Requirements:
Qualifications/Experience:
Master of Engineering – Data Science / Equivalent relevant hands-on experience.
Essential Skills Requirements:
Technical knowledge – Required:
Solid knowledge of Data Science and Deep Learning core skills.
Familiarity with state-of-the-art Computer Vision techniques and algorithms.
Experience in building predictive models using deep learning frameworks like TensorFlow and PyTorch.
Good software engineering skills and highly proficient in Python.
Advantageous Skills Requirements:
Knowledge in tools such as Azure Machine Learning, Docker, GitOps, Kubernetes is a plus.
Solid knowledge of Data Science and Deep Learning core skills.
Good software engineering skills and highly proficient in Python.
Demonstrated problem-solving skills with the ability to apply deep learning algorithms in business scenarios.
Knowledge in tools such as Azure Machine Learning, Docker, GitOps, Kubernetes is a plus.
Desired Skills:
- Data Science
- Deep Learning
- Computer Vision techniques