over 2 years ago
Delhi, IndiaStaff+
Responsibilities
- Design and develop ensembles of classical and deep learning algorithms for complex enterprise interactions.
- Design and implement statistical models for enterprise cybersecurity risk.
- Apply data-mining, AI, graph analysis, relevance, and recommendation techniques to product problems.
- Build production-quality solutions balancing complexity and performance.
- Participate in the engineering lifecycle by designing ML infrastructure and data pipelines, writing production code, conducting code reviews, and collaborating with infrastructure and reliability teams.
- Drive the architecture and use of open-source numerical computation and machine learning libraries.
- Collaborate with data engineering, frontend, product management, and DevOps teams while documenting work and facilitating teamwork.
Requirements
- Ph.D. or M.S. in Computer Science or Electrical Engineering with hands-on software engineering experience.
- At least 5 years of experience in machine learning and Python programming.
- Expertise in programming concepts and building large-scale systems.
- Knowledge of state-of-the-art algorithms, statistical analysis, and modeling.
- Strong understanding of NLP, probabilistic graphical models, deep learning with graph structures, and model explainability.
- Foundational knowledge of probability, statistics, and linear algebra.
- Ability to handle complex and ambiguous problems, learn quickly, iterate, and take ownership.
- Product focus, collaboration skills, strong communication, and interest in building usable systems.
Categories
About Balbix
Balbix builds an enterprise cyber risk and exposure management platform that unifies data from 150+ security and IT tools to inventory assets, prioritize vulnerabilities by business impact, and quantify risk in dollars. It sells its software to security teams such as CISOs and vulnerability management leaders, often in large enterprises. Founded in 2015 and headquartered in San Jose, Balbix was acquired by Safe Security.