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At Balbix we believe in using the right algorithms and tools to ensure correctness, performance and deliver an excellent user experience. We draw boldly from the latest in AI/ML research but are unafraid to go beyond Bayesian inference and statistical models if the situation demands it. We are generalists, caring as much about storytelling with data, as about bleeding edge techniques, scalable model training and deployment. We are building a data science culture with equal emphasis on knowing our data, grokking security-first principles, caring about customer needs, explaining our model predictions, deploying at scale, communicating our work, and adapting the latest advances.
Job Responsibility:
Design and develop an ensemble of classical and deep learning algorithms for modeling complex interactions between people, software, infrastructure and policies in an enterprise environment
Design and implement algorithms for statistical modeling of enterprise cybersecurity risk
Apply data-mining, AI and graph analysis techniques to address a variety of problems including modeling, relevance and recommendation
Build production quality solutions that balance complexity and performance
Participate in the engineering life-cycle at Balbix, including designing high quality ML infrastructure and data pipelines, writing production code, conducting code reviews and working alongside our infrastructure and reliability teams
Drive the architecture and the usage of open source software library for numerical computation such as TensorFlow, PyTorch, and ScikitLearn
Requirements:
Ph.D. in Computer Science and Engineering or related field
3+ years of experience in the field of Machine Learning, programming in Python, and building scalable distributed systems
Foundational knowledge of probability, statistics and linear algebra
Expertise in state-of-the-art AI algorithms such as deep-learning, NLP, probabilistic graphical models, graphical algorithms, reinforcement learning and time-series analysis
Knowledge of statistical analysis and modeling techniques, and model explainability
Nice to have:
Able to take on very complex problems, learn quickly, iterate, and persevere towards a robust solution
Product-focused and passionate about building truly usable systems
Collaborative and comfortable working across teams including data engineering, front end, product management, and DevOps
Responsible and like to take ownership of challenging problems
A good communicator, and facilitate teamwork via good documentation practices
Comfortable with ambiguity and thrive in designing algorithms for evolving needs
Intuitive in using the right type of models to address different product needs
Curious about the world and your profession, constant learner