Balbix22mo ago

AI/ML Architect

Delhi NcrFull-Timemid

Data ScienceOtherArchitectConstruction & Real Estate

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Quick Summary

Overview

WHO WE ARE Balbix is the world's leading platform for cybersecurity posture automation. Using Balbix, organizations can discover,

Technical Tools

pythonpytorchtensorflowcode-reviewcybersecuritydeep-learningdistributed-systemsetlmachine-learningstatistical-modeling

WHO WE ARE

Balbix is the world's leading platform for cybersecurity posture automation. Using Balbix, organizations can discover, prioritize and mitigate unseen risks and vulnerabilities at high velocity. With seamless data collection and petabyte-scale analysis capabilities, Balbix is deployed and operational within hours, and helps to decrease breach risk immediately.

Balbix counts many global 1000 companies among its rapidly growing customer base. We are backed by John Chambers (the former CEO and Chairman of Cisco), top Silicon Valley VCs and global investors. We have been called magical, and have received raving reviews as well as customer testimonials, numerous industry awards, and recognition by Gartner as a Cool Vendor, and by Frost & Sullivan.

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.

This role is open for Bengaluru/Gurugran.

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

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

A 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