Assist in inventing, designing, developing, and evaluating innovative models on large-scale data.
Support the design and implementation of scalable, efficient, automated Machine Learning pipelines.
Contribute to innovation projects from idea to implementation under guidance.
Collaborate closely with software engineering teams and customers to understand project requirements.
Be eager to learn about cybersecurity data analytics and related tools.
Help communicate results through internal reports, and blogs, and assist in preparing for scientific papers and conference presentations.
Requirements & Skills:
Currently pursuing a degree in Computer Science, Data Science, Machine learning, or a related field
Proficient in English
A basic understanding of coursework in software engineering is a plus.
Experience with coursework in one or more of the following Machine Learning fields: supervised, semi-supervised, or unsupervised learning, explainability of models, advanced statistics, graph theory, and game theory.
Strong logical reasoning and problem-solving skills.
Enthusiasm for completing tasks and making projects successful.
Hands-on experience with sci-kit-learn, Pandas, PyTorch, (py)Spark will boost the start
