Senior AI Engineer

3 Minutes ago • All levels • Research Development

Job Summary

Job Description

We are seeking an experienced AI/ML Engineer to join our team, focusing on building and optimizing machine learning models for threat detection within Google Workspace's email production suite. This role involves designing feature engineering pipelines, building and fine-tuning deep learning and traditional ML models to detect malicious intent in emails, and managing the complete machine learning lifecycle using MLFlow. The ideal candidate will work with large-scale datasets, collaborate with security analysts, and optimize Spark-based data processing.
Must have:
  • 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.
  • 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.
Good to have:
  • Experience with Google Cloud Platform (GCP) and BigQuery.
  • Background in cybersecurity or threat intelligence.
  • Experience in building models for real-time inference systems.
Perks:
  • Access to trainings and certifications
  • Bonuses and aids
  • Socializing activities
  • Attractive compensation
  • Work on a high-impact platform used by millions of Gmail users globally
  • Collaborate with a talented team of engineers, data scientists, and security professionals
  • Opportunity to shape next-generation email threat detection using cutting-edge AI/ML
  • Work culture based on diversification, inclusion, and authenticity

Job Details

Description

Position at Ness Digital Engineering

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.

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.

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.

Nice to Have

  • Experience with Google Cloud Platform (GCP) and BigQuery.
  • Background in cybersecurity or threat intelligence.
  • Experience in building models for real-time inference systems.

Why Join Us?

  • Work on a high-impact platform used by millions of Gmail users globally.
  • Collaborate with a talented team of engineers, data scientists, and security professionals.
  • Opportunity to shape next-generation email threat detection using cutting-edge AI/ML.

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.

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