Ml Postdoc Researcher - Llms & Generative Ai (AI)

TL;DR

ML Postdoc Researcher (AI): Contributing to innovative projects in the field of Large Language Modeling (LLM) and clinical data analysis with an accent on developing novel algorithms and methodologies for generative modeling tasks. Focus on implementing, training, and fine-tuning LLM and GPT-like models on large-scale datasets to ensure optimal performance and accuracy.

Location: Participation in the Postdoctoral Research program requires that you are physically present in the United States for the duration of the program.

Salary: $50-$60 per hour

Company

hirify.global is the world’s first health provider led data platform with a vision of Saving Lives with Data.

What you will do

• Collaborate with researchers and engineers to design, develop, and refine large language models and generative models for various applications.
• Utilize your expertise in machine learning and natural language processing to develop novel algorithms and methodologies for generative modeling tasks.
• Implement, train, and fine-tune LLM and GPT-like models on large-scale datasets to ensure optimal performance and accuracy.
• Stay up to date with the latest research advancements and techniques in the field of language modeling, generative modeling, and machine learning.
• Deliver the next generation of innovation in trustworthy healthcare.

Requirements

• Ph.D. in Computer Science, Electrical Engineering, or a related field, with a focus on machine learning, natural language processing (NLP), Large Language Models (LLMs), multi-modal foundation models, and generative AI
• Strong theoretical and practical background in NLP including experience with state-of-the-art architectures
• Proficiency in deep learning frameworks (e.g., PyTorch, TensorFlow, etc.) and libraries commonly used in NLP and Generative AI
• Solid programming skills in Python and the ability to write clean, efficient, and well-documented code
• Excellent problem-solving and troubleshooting abilities, along with a strong analytical mindset and persistence in resolving problems
• Strong communication skills and the ability to work effectively in a collaborative research environment

Nice to have

• Experience with distributed parallel training, large-scale multi-modal foundation and generative models
• Familiarity with parameter-efficient tuning techniques, Reinforcement Learning from Human Feedback (RLHF), and prompt engineering techniques
• Familiarity with training multi-modal foundation models
• Familiarity with cloud-based infrastructure and experience deploying large-scale machine learning models in production environments
• A track record of publications and contributions to the machine learning and natural language processing communities

Culture & Benefits

• Competitive compensation
• Company-issued laptop and equipment
• Opportunities for future full-time positions