Applied AI Engineer, Public Health LLMs at Resolve to Save Lives

Position Purpose

• We are looking for a passionate Applied AI Engineer to join our innovative team, focusing on the exciting field of Large Language Models (LLMs) in the context of Public Health. In this role, you will lead the design, fine-tuning, deployment, and evaluation of AI/ML systems based on pre-trained models (e.g., LLaMA, Mistral, GPT, Phi) that help ease the lives of healthcare workers and clinicians. You will work closely with back-end and mobile engineers to bring cutting-edge AI capabilities to life.
• The ideal candidate will possess the expertise to leverage existing Large Language Models (LLMs) to train and evaluate models using program-specific clinical data (e.g., patient notes, SMS interactions, training materials or health worker feedback) and deploy within RTSL's digital health tools and global EHRs (e.g., Simple, BP Passport).Additionally, there is a strong likelihood of developing an open-source, locally runnable, adapted LLM to address cost and confidentiality concerns.

You'll Be Working At The Intersection Of Cutting-edge AI And Grassroots Public Health. This Is An Opportunity To Shape The Future Of Digital Health Tools That Are Open Source, Impactful, Real-world Solutions For Some Of The Most Underserved Populations Globally. Our Primary Use Cases For LLMs Are Anticipated To Include (not Limited To)

• Generating patient summaries specifically tailored for healthcare workers.
• A chatbot for appointment scheduling.
• Develop a predictive model to enhance and automate existing workflows.
• Optimized worklists for frontline workers.
• On-the-job training and ready-reckoner tools for healthcare professionals.

Length of Engagement: This is a two-year fixed-term appointment with the possibility of extension based on available funding and mutual interest.

Core Responsibilities

The ideal candidate will perform duties and responsibilities such as, but not limited to, the following:

• Research, evaluate, and implement state-of-the-art LLMs.
• Fine-tune pre-trained models for specific tasks and datasets.
• Develop and deploy AI applications using Python.
• Perform data manipulation and analysis using Pandas to prepare data for model training and evaluation.
• Design and evaluate prompt engineering strategies for optimizing LLM outputs in specific public health contexts.
• Collaborate with cross-functional teams to integrate AI solutions into existing products and workflows.
• Stay up to date with the latest advancements in AI, particularly in the LLM space.
• Apply responsible AI principles, including fairness, privacy, and transparency, especially in clinical and community health settings.
• Manage and lead the AI pilots/projects at RTSL.
• Train and upskill other engineers on the team.

Qualifications
Education

• Bachelor's or Master's degree in Computer Science, Engineering, Machine Learning or a related field

Experience

• 8 years of software development experience
• 3-5 years of experience in training and using AI models.
• Proven track record of using Large Language Models (LLMs) and building Predictive Models to meet user requirements
• Experience collaborating with multi-disciplinary and cross-functional teams
• Delivered LLM-based solutions in resource-constrained environments
• Hands-on experience with pre-trained AI models.
• Experience working in healthcare or public health settings (strong plus)
• Contributed to or maintained open-source AI/ML projects (strong plus).
• Familiarity with MLOps including model serving, performance monitoring, and lifecycle management, particularly in low-bandwidth or edge environments i(s a plus).

Skills & Abilities

• Strong proficiency in Python programming.
• Strong experience in data manipulation using Pandas, NumPy, and data preprocessing techniques
• Familiarity with pre-train models
• Skilled in machine learning frameworks (e.g., TensorFlow, PyTorch).
• Familiarity with AI Tools (Hugging Face, LangChain, ONNX, etc.)
• Strong understanding of AI ethics, data privacy, and bias mitigation techniques
• Excellent analytical and problem-solving skills
• Ability to communicate complex technical ideas clearly to non-technical stakeholders
• Ability to prototype and iterate quickly
• Comfortable working in agile, interdisciplinary teams across geographies