ML Engineer

About The Company

ISC2 is a leading nonprofit member organization dedicated to cybersecurity professionals worldwide. Guided by core values of Integrity, Advocacy, Commitment, Inclusion, and Excellence, ISC2 strives to create a safe and secure cyber world. The organization offers a globally recognized, award-winning portfolio of certifications that validate cybersecurity knowledge, skills, and experience across all career levels. ISC2’s charitable arm, the Center for Cyber Safety and Education, furthers its mission by educating vulnerable populations about cyber risks and promoting access to cybersecurity careers. ISC2 is committed to fostering an inclusive and equitable environment that values diverse perspectives and experiences, creating a culture of authenticity, trust, empowerment, and connectedness among its global cybersecurity community. Learn more about ISC2 and its initiatives online and through social media platforms.

About The Role

ISC2 is seeking a Lakehouse Machine Learning (ML) Engineer to develop and maintain a modern data lakehouse platform and implement machine learning solutions that support the membership business. This role covers the entire data lifecycle—from building robust data pipelines to deploying and monitoring machine learning models in production. The engineer will work primarily with Python and Spark on Azure Databricks or comparable platforms, focusing on data exploration, feature engineering, model development, and delivering actionable insights to stakeholders. The position offers opportunities to engage with advanced topics such as applied Large Language Models (LLMs) as the platform evolves. The candidate will ensure that all work complies with security, governance, and data protection standards. This role requires collaboration across teams and the ability to translate complex analytical results into clear business value. Note: This position is not open to residents of California.

Qualifications

• Strong ETL skills with the ability to assemble datasets independently.
• Proficiency in Python and SQL, with experience across enterprise source systems.
• Experience using standard ML libraries such as scikit-learn and at least one deep learning framework (PyTorch or TensorFlow).
• Comprehensive understanding of machine learning methodologies, including survival analysis, forecasting, classification, causal inference, and sequence modeling.
• Familiarity with hyperparameter tuning, cross-validation, model validation, bias mitigation, and uncertainty quantification.
• Ability to explain complex models and results to non-technical stakeholders and executives.
• Knowledge of data security, privacy, compliance, and governance frameworks affecting member data.
• Experience with Databricks platform components such as Unity Catalog, Workflows, and MLflow is a plus.
• Experience with cohort-based or hierarchical forecasting and Salesforce is advantageous.
• Relevant certifications such as Databricks Data Engineer or Machine Learning Associate/Professional, Azure AI Engineer, or Data Scientist Associate are a plus.
• Bachelor’s or Master’s degree in IT or related field preferred; candidates with a high school diploma and 7+ years of relevant experience will also be considered.
• Minimum of 3 years of hands-on experience in data engineering and applied machine learning in enterprise environments.
• Proven experience deploying and maintaining ML models in production environments using MLflow or equivalent tools.
• Experience building and operating within a medallion architecture (bronze, silver, gold layers) in a governed data environment using distributed processing engines like Spark.
• Practical experience with Large Language Models, membership lifecycle data, and build-versus-buy evaluations is desirable.
  
  

Responsibilities

• Develop and maintain Python and Spark data pipelines spanning bronze, silver, and gold layers, including semantic datasets and machine learning models.
• Conduct thorough data exploration to identify viable modeling opportunities and engineer features accordingly.
• Collaborate with stakeholders to prioritize analytical questions and define valuable use cases.
• Design, build, and deploy a variety of machine learning models including survival, forecasting, classification, sequence models, recommenders, and causal evaluation frameworks.
• Manage the full lifecycle of ML models in production, including experiment tracking, model registry, scheduled inference, and monitoring for model drift and decay.
• Deliver actionable insights by integrating model outputs into governed semantic tables that feed dashboards and customer data platforms, and effectively communicate results to business teams.
• Engage with applied Large Language Model use cases such as structured data extraction and information retrieval as the platform matures.
• Ensure all development adheres to platform security, governance, access controls, data protection, auditability, and human-in-the-loop review processes.
• Create reusable patterns, project templates, and implementation standards to streamline future model development efforts.
• Conduct small-scale proofs of concept to validate data feasibility, approach soundness, and operational viability before full-scale implementation.
• Perform miscellaneous duties as assigned to support team and organizational goals.
  
  

Benefits

• Competitive salary range of $94,000 to $118,900 per year, commensurate with experience and qualifications.
• Comprehensive benefits package details available at ISC2’s global benefits webpage.
• Opportunities for professional growth and development within a mission-driven organization.
• Remote work flexibility with minimal travel requirements (up to 5%).
  
  

Equal Opportunity

We are proud to be an Equal Employment Opportunity employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, or any other basis protected by federal, state, or local law.