Staff AI Engineer

About This Role

As a Staff AI Engineer, you will work with petabyte-scale data from various sources, including Balbix's proprietary sensors and third-party threat feeds. You will utilize a range of AI techniques such as deep learning, probabilistic graphical models, graph learning, recommendation systems, reinforcement learning, and NLP. You will be a key contributor to building a world-class product that addresses significant challenges in the technology industry.

Data Science at Balbix

At Balbix, we are committed to using the most effective algorithms and tools to ensure accuracy, optimize performance, and deliver an exceptional user experience. We embrace cutting-edge AI/ML research and are willing to go beyond traditional Bayesian inference and statistical models when necessary. Our team comprises generalists who are equally adept at data storytelling, applying advanced techniques, scalable model training, and deployment.

We are cultivating a data science culture that values a deep understanding of our data, security first principles, customer needs, model explainability, scalable deployment, effective communication, and the adoption of the latest advancements.

We foster a supportive environment where team members look out for each other, enjoy working together, and maintain open communication channels on all matters, both technical and non-technical.

Responsibilities

• Design and develop ensemble models using classical and deep learning algorithms to represent complex interactions within enterprise environments involving people, software, infrastructure, and policies.
• Design and implement algorithms for the statistical modeling of enterprise cybersecurity risk.
• Apply data-mining, AI, and graph analysis techniques to solve problems related to modeling, relevance, and recommendations.
• Build production-ready solutions that effectively balance complexity and performance.
• Participate in the end-to-end engineering lifecycle, including designing robust ML infrastructure and data pipelines, writing production-level code, conducting code reviews, and collaborating with infrastructure and reliability teams.
• Drive the architecture and utilization of open-source software libraries for numerical computation, such as TensorFlow, PyTorch, and Scikit-learn.

What You Bring

• The ability to tackle highly complex problems, learn rapidly, iterate effectively, and persevere towards robust solutions.
• A product-focused mindset with a passion for building highly usable systems.
• A collaborative spirit, comfortable working across diverse teams including data engineering, front-end development, product management, and DevOps.
• A strong sense of responsibility and a proactive approach to ownership of challenging problems.
• Excellent communication skills to facilitate teamwork and maintain good documentation practices.
• Comfort with ambiguity and a talent for designing algorithms for evolving requirements.
• Intuition in selecting the appropriate models for various product needs.
• A curious and continuous learning mindset towards the world and your profession.

Qualifications

• Ph.D. or M.S. in Computer Science or Electrical Engineering, coupled with hands-on software engineering experience.
• 5+ years of experience in Machine Learning and proficiency in Python programming.
• Expertise in programming concepts and experience building large-scale systems.
• Knowledge of state-of-the-art algorithms, combined with expertise in statistical analysis and modeling.
• A solid understanding of NLP, Probabilistic Graphical Models, Deep Learning with graph structures, and model explainability.
• Foundational knowledge of probability, statistics, and linear algebra.