Senior Machine Learning Engineer

Responsibilities

• Lead the training, testing, and optimization of machine learning models for cybersecurity and malware, owning technical decisions end to end.
• Evaluate and select model architectures across classical machine learning and deep learning.
• Drive data exploration, feature engineering, and preprocessing across large structured and unstructured datasets.
• Design and own model evaluation pipelines, including validation strategies, benchmarking, and performance analysis.
• Partner with data engineers and threat researchers to improve data quality, feature sets, and model performance.
• Own the deployment, integration, and monitoring of machine learning models in production.
• Define and improve scalable machine learning workflows and model development lifecycle practices.
• Translate ambiguous business and product requirements into machine learning strategies and solutions.
• Mentor junior and mid-level engineers.
• Influence research and product direction for machine learning in critical-infrastructure security.

Requirements

• Degree in Computer Science, Mathematics, Engineering, AI, or a related field; an advanced degree is a plus.
• 5+ years of hands-on machine learning experience, including a track record of shipping models to production.
• Deep understanding of machine learning algorithms, model training, evaluation techniques, and optimization methods.
• Strong Python skills and expertise with common machine learning libraries.
• Experience with data exploration, feature engineering, and real-world datasets at scale.
• Strong command of model evaluation metrics and validation strategies.
• Experience deploying and integrating machine learning models into production systems.
• Experience with cloud platforms, preferably AWS.
• Familiarity with MLOps practices and tools.
• Demonstrated technical leadership, including mentoring, architecture decisions, and setting standards.
• Experience in cybersecurity, malware analysis, or a related security domain is a strong plus.
• Strong problem-solving skills, attention to detail, and a bias toward experimentation.
• Excellent communication and cross-functional collaboration skills.

Benefits

• The role focuses on machine learning for critical-infrastructure cybersecurity and malware protection.