Generative AI Engineer - Model Optimization & Evaluation
Description For Generative AI Engineer - Model Optimization & Evaluation
RegScale, a leading continuous controls monitoring (CCM) platform, is seeking a Generative AI Engineer specializing in model optimization and evaluation. This role sits at the intersection of cutting-edge AI development and practical deployment challenges, focusing on making transformer-based models more efficient and effective in both cloud and on-premises environments.
The ideal candidate will be deeply experienced in the ML lifecycle, with particular expertise in model quantization, fine-tuning, and evaluation techniques. You'll be working on pushing the boundaries of what's possible in AI deployment efficiency, balancing performance with resource constraints across various computing environments.
Key aspects of the role include optimizing transformer models through techniques like quantization and pruning, developing comprehensive evaluation frameworks, and collaborating with domain experts on dataset engineering. You'll be responsible for making critical architectural decisions that impact model deployment across different environments, from cloud to edge computing scenarios.
The position requires both technical depth in AI/ML and the ability to communicate complex technical concepts to various stakeholders. You'll need to stay current with the latest advancements in model compression and efficient inference while maintaining a practical focus on production-grade implementations.
This is an excellent opportunity for an experienced AI engineer who wants to work on challenging problems in model optimization while contributing to a platform that delivers significant value in the governance, risk, and compliance space. The role offers the flexibility of remote work while being part of a team that's pushing the boundaries of AI efficiency and effectiveness.
Responsibilities For Generative AI Engineer - Model Optimization & Evaluation
- Design, fine-tune, and optimize transformer-based models focusing on quantization, distillation, pruning, and compression techniques
- Profile models and optimize performance across different hardware
- Develop and maintain rigorous model evaluation pipelines
- Work with domain experts to source, label, clean, and structure high-quality datasets
- Stay current with advancements in model compression and efficient inference
- Document experiments, design decisions, and trade-off analyses
Requirements For Generative AI Engineer - Model Optimization & Evaluation
- PhD OR Master's Degree plus 3+ years of progressive experience
- Strong understanding of transformer-based architectures
- Experience with model optimization: quantization, pruning, distillation
- Familiarity with deployment trade-offs
- Understanding of CUDA basics
- Hands-on experience with fine-tuning language models
- Proficiency with PyTorch
- Experience with Linux, SSH, scripting
- Strong written and verbal communication skills
- Experience designing evaluation protocols
- Experience with automated benchmarking and robustness testing
