ABOUT THIS ROLE
As a Staff AI Engineer you will get to play with petabyte data gathered from a multitude of data sources including Balbix proprietary sensors and 3rd party threat feeds. You will leverage a variety of AI techniques including deep learning, probabilistic graphical models, graph learning, recommendation systems, reinforcement learning, NLP, etc. And of course, you will be part of a team building a world-class product addressing one of the grand challenges in the technology industry.
DATA SCIENCE AT BALBIX
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.
We look out for each other, enjoy each others’ company, and keep an open channel of communication about all things data and non-data.
You will:
- 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
You are:
- 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
You have:
- A Ph.D./M.S. in Computer Science or Electrical Engineering with hands-on software engineering experience
- 5+ years of experience in the field of Machine Learning and programming in Python.
- Expertise in programming concepts and building large scale systems.
- Knowledge of state-of-the-art algorithms combined with expertise in statistical analysis and modeling.
- Robust understanding of NLP, Probabilistic Graphical Models, Deep Learning with graphs structures, model explainability, etc.
- Foundational knowledge of probability, statistics and linear algebra
