WHY NESS

We know that people are our greatest asset. Our staff’s professionalism, innovation, teamwork, and dedication to excellence have helped us become one of the world’s leading technology companies. It is these qualities that are vital to our continued success. As a Ness employee, you will be working on products and platforms for some of the most innovative software companies in the world.
You’ll gain knowledge working alongside other highly skilled professionals that will help accelerate your career progression.
You’ll also benefit from an array of advantages like access to trainings and certifications, bonuses, and aids, socializing activities, and attractive compensation.

REQUIRED SKILLS AND EXPERIENCE

• Proven expertise in feature engineering and model development for NLP, anomaly detection, or security domains.
• Strong programming skills in Python with hands-on experience in PyTorch for model development.
• Experience with Apache Spark (PySpark) for distributed data processing.
• Deep understanding of MLFlow for model tracking, versioning, and deployment.
• Strong background in machine learning theory, model evaluation, and productionization.
• Experience working with large datasets, especially from enterprise platforms like Google Workspace.
• Knowledge of common threat detection techniques and email-based attack vectors is a plus.

NOT CHECKING EVERY SINGLE REQUIREMENT?

If this role sounds good to you, even if you don’t meet every single bullet point in the job description, we encourage you to apply anyway. For most of the candidates that applied, we found a role that was a very good fit with their skills.
Let’s meet and you may just be the right candidate for one of our roles.
At Ness Digital Engineering we are willing to build a work culture that is based on diversification, inclusion, and authenticity

ABOUT THE ROLE

We are looking for an experienced AI/ML Engineer with deep expertise in feature engineering and model engineering to join our team supporting a global email production suite used across Google Workspace (Gmail). The core mission is to build and optimize machine learning models that can detect and prevent threats embedded in email content, attachments, and metadata.
You will work with large-scale datasets derived from enterprise Gmail environments and contribute to enhancing threat detection capabilities. The ideal candidate has hands-on experience with PyTorch, Spark (Python-based), and MLFlow for model lifecycle management.

KEY RESPONSIBILITIES

• Design and implement robust feature engineering pipelines to extract meaningful signals from structured and unstructured email data.
• Build and fine-tune deep learning and traditional ML models to detect malicious intent in emails (e.g., phishing, malware).
• Collaborate with security analysts and data engineers to define threat patterns and data labeling strategies.
• Use MLFlow to manage the complete machine learning lifecycle including experimentation, reproducibility, deployment, and monitoring.
• Optimize Spark-based data processing pipelines to efficiently handle large-scale datasets.
• Conduct offline and online evaluations of model performance using appropriate metrics.
• Stay updated on the latest advancements in AI/ML and apply them to continuously enhance the detection models.