Description
Designing, developing, and researching Machine Learning systems, models, and schemes
- Studying, transforming, and converting data science prototypes
- Research and implement appropriate ML algorithms and tools
- Performing statistical analysis and using results to improve models.
- Analyzing the use cases of ML algorithms and ranking them by their success probability
- Verifying data quality and/or ensuring it via data cleaning.
- Understand and use computer science fundamentals, including data structures, algorithms, computability, and complexity, and computer architecture
- Use exceptional mathematical skills, in order to perform computations and work with the algorithms involved in this type of programming
- Collaborate with data engineers to build data and model pipelines
- Analyse large, complex datasets to extract insights and decide on the appropriate technique
- Research and implement best practices to improve the existing machine-learning infrastructure
Requirements:
- Bachelor’s degree in Engineering, Computer Science (or equivalent experience)
- 2-5 years of relevant Software, ML, experience
- 2-5 years of experience in Python code writing.
- Good experience in using version control systems (eg. GIT)
- Good knowledge of ML frameworks, libraries, data structures, data modeling, and software architecture.
- Advanced proficiency with machine learning frameworks Tensorflow, Keras, PyTorch and libraries (like scikit-learn, open-CV)
- Good understanding of computer vision tasks, libraries, frameworks
- Good knowledge of mathematics, statistics, and algorithms.
- analytical and problem-solving abilities.
- Good communication and collaboration skills.
- Good knowledge of Docker.
- Experience with Cloud Services.
- Good time management and organizational abilities.