Job Description

Machine Learning Engineer

Blue Hexagon is looking for talented and highly motivated individuals to join our machine learning and data analytics team. We are looking for machine learning experts with current experience in advance AI technologies to execute our vision for the next generation AI-based network defenses. Ideal candidate should have experience in supervised and unsupervised learning techniques and in particular deep learning. The successful candidate will work closely with development engineers and security researchers to improve detection efficacy of the product.

Candidate will be required to lead projects from architecture design all the way to model training, evaluation and fine tuning the final result to the desired characteristics.

You will be a key member of the ML team that helps develop and improve the core functionality of the product.

Responsibilities:

Develop scalable solutions based on the state-of-the-art in machine learning and AI methodologies.

Formulate real life problems using the latest advancements in machine learning techniques.

Contribute and take ownership of projects including research, design and development of the final product.

Collaborate with other researches and engineers in the team to deliver the final product.

Build libraries, modules and automation tools for accelerated research and development.

Evaluate the performance of the ML architecture and fine tune the final results to match target performance measures.

Follow the advancement in the field, attend conferences and stay in touch with the academic leaders in the field.

Basic Qualifications:

Ph.D. in Computer Science, Electrical Engineering, Mathematics, Statistics, Physics, or similar quantitative fields

2+ years of industry experience in machine learning and data science projects

Solid background in machine learning and AI methodology

Strong knowledge of probabilistic models, stochastic process and deep learning

Experience working with supervised, and unsupervised learning and anomaly detection techniques

Familiarity with advanced software development tools

Experience in working with one or few of machine learning and deep learning tools: Pytorch, Tensorflow, Keras

Strong programming skills in Python and/or C/C++

Preferred Qualifications:

Good knowledge and experience in time series analysis, CNN, RNN, and LSTM architectures

Knowledge of network security and malware detection is considered as a plus

Publication in top-tier conferences or journals such as NIPS, ICML, ICLR, AAAI, KDD, JMLR, PAMI

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