Principal Machine Learning Engineer

Job Description

Salary:

About Index Engines

Index Engines is the worlds leading AI-powered analytics platform for ransomware and datacorruption detection. Our flagship product, CyberSense, empowers organizations to detectcorruption quickly and recover data effectively. Join us in our mission to build technology thatstands as the last line of defense for data security.

The Role

We are seeking experienced Principal Machine Learning Engineers to lead the development,deployment, and maintenance of high-impact machine learning models. You will collaborateclosely with engineering, product, and support teams to solve complex data integritychallenges.

Core Responsibilities

Design, implement, and maintain ML models from concept through production,

especially for anomaly and ransomware detection.

Continuously retrain and tune models to improve performance and accuracy.

Evaluate models using appropriate metrics (e.g., recall, precision, F1, AUC).

Translate research concepts into robust production code.

Collaborate in a cross-functional Scrum team, contributing to full SDLC activities.

Write clean, efficient code in Python and/or C/C++ for a Linux environment.

Support integration, testing, and deployment of ML solutions.

Partner with QA and Support teams to ensure product quality and customer success.

Minimum Qualifications

10+ years of professional software development experience (minimum 7 years

acceptable).

3+ years of hands-on experience deploying and maintaining ML models in production.

Strong proficiency in Python and/or C/C++.

Deep understanding of algorithms, data structures, and Big O complexity.

Familiarity with OS-level concepts: memory management, I/O, concurrency.

Skilled in Linux scripting and automation.

Experience using ML tools such as pandas, scikit-learn, and CUDA.

Proven success in developing high-quality, scalable systems.

Experience collaborating in Agile/Scrum environments using Git, Jira, etc.

Preferred Experience

PhD in Computer Science, Machine Learning, or related field.

Domain experience in cybersecurity or fraud detection.

Understanding of deep learning (e.g., neural nets, transformers, LLMs) and advanced ML

techniques (e.g., GANs, RL).

Background in research or academic publishing is a plus.

What We Value

Analytical thinking and technical leadership.

Ability to communicate complex ideas clearly to non-experts.

Proactive problem-solving and openness to feedback.

Motivation to contribute to meaningful work in cybersecurity.

Independent initiative balanced with strong team collaboration.

Why Join Us?

Be part of a fast-growing innovator in cybersecurity and data protection.

Collaborate with a world-class team solving mission-critical challenges.

Competitive compensation and benefits.

Full-time