Description

Architect and implement state-of-the-art generative models for complex NLP tasks.

Responsibilities

• Design and implement generative models for text generation, completion, translation, and summarization.
• Develop data pipelines to evaluate and preprocess large-scale datasets for model training.
• Collaborate with software engineers to deploy and optimize models for scalability and real-time performance.
• Build and implement guardrails for both open-source and cloud-native LLMs.
• Articulate model behavioral analysis and hallucination effects to business stakeholders.

Required Skills

• 15+ years of experience in Data Science, Machine Learning, and NLP technologies.
• Deep expertise in Transformer Encoder Networks and LLM architectures.
• Extensive knowledge of generative modeling including GANs, VAEs, and transformer-based architectures.
• Proven experience in model development, serving, and training/re-training in data-sparse environments.
• Advanced proficiency in prompt engineering for instruction-based LLMs.
• Ability to apply deep learning and generative modeling techniques to solve AI problems.
• Experience with large-scale dataset preprocessing and data integrity management.
• Strong understanding of model behavioral analysis and hallucination mitigation.

Preferred Skills

• Contributions to the research community via publications or conference presentations.
• Experience providing technical guidance and mentorship to junior data scientists.

Key Skills

Education

ANY GRADUATE