Must have experience working in the Life Sciences or Healthcare industry.
Design and oversee AWS cloud architectures optimized for advanced LLM usage, ensuring scalability and robustness of NLP applications.
Implement and maintain LLM-focused NLP projects from ideation through production deployment, emphasizing innovation in LLM capabilities like Llama3 and Qwen, and leveraging frameworks like Hugging Face.
Collaborate with data scientists, NLP engineers, cloud specialists, and software developers, ensuring effective implementation and integration of LLMs and Hugging Face tools.
Develop strategies for cloud-based NLP solutions that ensure cost-efficiency, security, and compliance while supporting rapid model experimentation and deployment using AWS and Hugging Face.
Maintain rigorous performance standards for LLM-based models, constantly seeking enhancements in model accuracy and operational efficiency.
Work closely with IT security to ensure stringent data protection standards are met in the deployment and operation of LLMs and related software on AWS.
Analyze computational resource utilization on AWS, optimizing for cost and performance throughout the lifecycle of LLM development and application.
Stay updated on the forefront of LLM technologies and tools like Hugging Face, alongside AWS advancements, bringing in industry-leading practices to maintain a competitive edge.
Regularly deliver impactful insights and updates to the relevant stakeholders, highlighting the strategic value and progress of NLP initiatives.
Explore emerging trends in NLP and LLM advancements, aiming to leverage new potential applications and improve existing systems.
Requirements & Skills:
Experience working in the Life Sciences or Healthcare industry. (REQUIRED)
Bachelor’s or Master’s in computer science, Data Science, or related fields, with a strong focus on NLP/LLM and cloud solutions.
Minimum of 2 years in NLP systems development and operations, including extensive experience with AWS and expert knowledge of LLMs such as Llama3 and Qwen and familiarity with implementation frameworks like Hugging Face.
Expert proficiency in Python and familiarity with advanced NLP frameworks and libraries.
Proven track record in the successful deployment of large-scale NLP solutions in the healthcare or life sciences industry, particularly those involving advanced LLM technologies.
Strong analytical and communication skills, adept at working on multiple projects in a dynamic environment.
Experience dealing with protected health information (PHI) and familiarity with healthcare-related data privacy laws such as HIPAA.
Experience in working with AWS cloud environment and large databases (e.g., AWS redshift).
Experience in managing ML lifecycle using open-source tools (e.g., MLflow).
