Generative AI Engineer - Model Optimization & Evaluation - Remote

Overview

RegScale is a continuous controls monitoring (CCM) platform purpose-built to deliver fast and efficient GRC outcomes. We help organizations break out of the slow and expensive realities that plague legacy GRC tools by bridging security, risk, and compliance through controls lifecycle management. By leveraging CCM, organizations experience massive process improvements like 90% faster certification times, and 60% less audit prep time. Today’s expansive security and compliance requirements can only be met with a modern, CCM based approach, and RegScale is the leader in that space.

In Short

• Building next-generation automation capabilities with AI.
• Focusing on model quantization, fine-tuning, and evaluation.
• Optimizing transformer-based model workflows for various environments.
• Understanding the ML lifecycle from data preparation to model evaluation.
• Collaborating with engineers and product leaders.
• Developing rigorous model evaluation pipelines.
• Working with domain experts on high-quality datasets.
• Staying current with advancements in model compression and inference.
• Documenting experiments and sharing findings with stakeholders.
• Hands-on experience with fine-tuning language models.

Requirements

• PhD or Master's Degree plus 3+ years of experience.
• Strong understanding of transformer-based architectures.
• Experience with model optimization techniques.
• Familiarity with deployment trade-offs in ML.
• Ability to debug performance issues across environments.
• Hands-on experience with PyTorch.
• Experience with Linux and remote machine operations.
• Strong communication skills for documentation.
• Experience designing evaluation protocols.
• Experience with automated benchmarking.

Benefits

• Opportunity to work on cutting-edge AI projects.
• Collaborative work environment with experts.
• Flexible work arrangements including remote options.
• Access to the latest tools and technologies in AI.
• Professional development opportunities.