Applied AI Scientist

Position Summary

League is seeking an Applied AI Scientist to join our AI Models team, focused on advancing innovation in small language models (SLMs) and applied AI systems.

This role sits at the intersection of research and engineering, with a strong emphasis on experimentation, model development, and applied system design. You will work closely with AI leadership to explore, prototype, and operationalize new approaches to domain-specific language models that power League's healthcare platform.

Unlike a traditional engineering role, this position is R&D-focused, designed for someone who can:

• Translate emerging research into practical implementations
• Rapidly experiment with model architectures and optimization techniques
• Leverage modern AI tools and frameworks to accelerate development

You will contribute to building League's next generation of AI capabilities, while partnering with platform and product teams to bring high-impact innovations into production.

In this role, you will:

Model Development & Experimentation

• Design and implement experiments across fine-tuning, distillation, and optimization of small language models (1–10B parameters)
• Rapidly prototype and evaluate new approaches to model performance, efficiency, and reasoning quality
• Leverage modern tooling and AI-assisted workflows to accelerate iteration cycles

Applied AI & Systems Integration

• Build applied systems that connect models, data pipelines, and evaluation frameworks
• Focus on “wiring together” components across model training, evaluation, and deployment workflows
• Collaborate with engineering teams to transition promising experiments into production environments

Data & Training Strategy

• Contribute to training data design, including curation, labeling strategies, and synthetic data generation
• Work with data partners to explore AI-driven insights and improvements to model performance

Evaluation & Model Quality

• Define and run experiments to assess model performance across accuracy, reasoning, and safety dimensions
• Contribute to building lightweight evaluation frameworks and benchmarking approaches

AI-Native Development Practices

• Actively leverage AI tools (e.g., Copilot, LLM-assisted coding, research copilots) to improve productivity and experimentation speed
• Document and share workflows that improve how the team builds and evaluates models

Cross-Functional Collaboration

• Partner with Product, Platform Engineering, and AI Orchestration teams to integrate models into real-world use cases
• Communicate complex technical concepts clearly to cross-functional stakeholders

About you:

• 5+ years of experience in AI/ML, with a focus on model development, NLP, or applied research
• Strong programming skills in Python and experience with deep learning frameworks (PyTorch, TensorFlow, JAX)
• Hands-on experience with LLM fine-tuning, distillation, or optimization techniques (e.g., LoRA, RLHF, quantization)
• Experience working with SLMs (1-10B parameters) and deploying models in production environments
• Familiarity with data pipeline design, synthetic data generation, and evaluation frameworks
• Ability to rapidly prototype and iterate on AI experiments
• Excellent communication skills and ability to work cross-functionally
• Bonus: Background in healthcare AI, NLP for clinical data, or experience with AI-driven healthcare applications