Overview
Remote
$60+
Contract - Independent
Contract - W2
Contract - 6 Month(s)
Skills
Apache Spark
Artificial Intelligence
PyTorch
PySpark
Python
Natural Language Processing
Machine Learning (ML)
Job Details
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:
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.
- 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.
- Experience with Google Cloud Platform (Google Cloud Platform) and BigQuery.
- Background in cybersecurity or threat intelligence.
- Experience in building models for real-time inference systems.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.