Lakehouse Machine Learning Engineer

🕒 September 18

🏄 California – Remote

🏄 California – Remote

💵 $93k - $118.9k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 Machine Learning Engineer

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ISC2

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 1989

🔒 Cybersecurity

📚 Education

☁️ SaaS

Cybersecurity • Education • SaaS

ISC2 is a leading organization dedicated to advancing cybersecurity education and certification. They provide various programs for individuals at different stages of their cybersecurity careers, including certification exams, training resources, and leadership development opportunities. ISC2 also advocates for members and promotes diversity within the cybersecurity field by empowering professionals and communities.

📋 Description

• Build and maintain Python/Spark pipelines through bronze, silver, and gold layers • Build semantic datasets and ML models that consume governed lakehouse data • Explore data before modeling, develop and test features, and coordinate with stakeholders on worthwhile analytical questions • Develop survival and time-to-event, forecasting, classification and propensity, sequence, recommender, and causal evaluation models • Deploy models to production and manage experiment tracking, model registry, scheduled inference, and monitoring for drift and decay • Deliver model outputs through governed semantic tables feeding dashboards and CDP systems • Explain analytical results to business teams • Take on applied LLM work, including structured extraction from free text and retrieval over governed data • Build within security and governance requirements, including access controls, data protection, auditability, and human review • Create reusable project templates, shared feature and evaluation code, and implementation standards • Develop proofs of concept to validate data support, analytical approaches, and operational viability • Perform miscellaneous duties as required

🎯 Requirements

• Strong Extract/Transform/Load (ETL) skills, with the ability to assemble a dataset rather than request one • Fluent Python and SQL skills • Experience working across enterprise source systems • Fluency with the standard ML stack, including scikit-learn and at least one deep learning framework such as PyTorch or TensorFlow • Knowledge of survival and time-to-event analysis, forecasting, classification and propensity, sequence models, recommenders, and causal evaluation • Familiarity with hyperparameter tuning and cross-validation • Ability to perform careful model validation, model evaluation, and bias mitigation • Ability to explain results to executives in non-technical terms • Understanding of data security, privacy, compliance, access controls, data protection, and auditability • Production experience with Databricks, including Unity Catalog, Workflows, MLflow, or comparable technologies; these are listed as a plus • Ability to perform cohort-based or hierarchical forecasting at scale, a plus • Working knowledge of Salesforce, a plus • Relevant Databricks or Azure certifications, or equivalent, a plus • Bachelor’s or Master's degree in an IT field preferred; candidates with a high school diploma or equivalent and 7+ years of hands-on experience may be considered • 3+ years of hands-on experience in data engineering and applied machine learning • Experience deploying and monitoring models in production • Experience with MLflow or an equivalent tracking, registry, and scheduled-inference stack • Production experience building in a medallion architecture or equivalent layered model in a data-catalog-governed environment • Experience with distributed processing using Spark or a comparable engine • Experience with an open table format such as Delta or Iceberg • Experience with catalog-managed schemas, lineage, and access control • Practical LLM experience including embeddings, retrieval, structured extraction, and evaluation, a plus • Experience with subscription or membership-lifecycle data, a plus • Experience running build-versus-buy evaluations, a plus • Up to 5% travel may be required • This position is not available to residents of California

🏖️ Benefits

• Up to 5% travel may be required • Work normal business hours and extended hours when necessary • Comprehensive benefits package (details linked in posting) • Inclusive and equitable work environment • Remote work environment