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About
Projects:
This role focuses on applying machine learning and LLMs to enhance IAM decision-making and automation. Engineers will build, train, and integrate LLM-based models that support access, risk evaluation, and governance use cases across internal IAM products. The environment is highly product-focused and supports advanced AI/ML-powered decisioning as part of IAM processes.
Responsibilities
• Design, build, and deploy ML applications and pipelines on GCP. • Develop and integrate ML and NLP/SLM solutions, including fine-tuning and production hosting. • Collaborate cross-functionally to deliver scalable, high-performance ML systems. • Support the full machine learning lifecycle from data preparation through model evaluation and deployment.
Required Qualifications
• 5+ years of experience as a
ML Engineer ; Strong proficiency in Python • Experience with
ML
and
AI , including
LLM development and integration • Experience
deploying and operating ML models in production environments • Hands-on experience building data-driven decision systems embedded in product workflows • Experience integrating
ML models via APIs
into internal platforms • Strong understanding of ML workflows, feature engineering, and model evaluation • Experience with common ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn) • Familiarity with hybrid cloud environments (public cloud and proprietary private cloud)
Preferred / Nice to Have
• Experience in Identity & Access Management (IAM) or Cybersecurity
Languages
- English
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