Senior Applied Researcher AI/ML (Medtech)

TL;DR

Senior Applied Researcher AI/ML (AI/ML): Developing and scaling AI/ML model systems for the healthcare market with an accent on GenAI and LLM-based approaches. Focus on building predictive models, summarization tools, and RAG pipelines integrated into large-scale SaaS production environments.

Location: Remote (US). Occasional travel to Mississauga or Salt Lake City offices for onboarding and team events is required.

Salary: $178,000 – $198,000 per year

Company

A leading founder-led health tech company providing a comprehensive platform for long-term and post-acute care provider organizations.

What you will do

• Apply GenAI and LLM-based techniques to develop model systems for large-scale cloud-based SaaS production environments.
• Collaborate with product leaders, clinical informaticists, and engineers to design and deliver high-value healthcare solutions.
• Build and evaluate solutions for predictive modeling, summarization, recommenders, semantic search, and classification.
• Execute R&D including data collection, cleaning, prompt tuning, parameter fine-tuning, and model training.
• Implement responsible AI evaluation practices using frameworks such as LLM-as-judge, RAGAS, and LangSmith.
• Contribute to a collaborative team culture by sharing knowledge and developing new organizational capabilities.

Requirements

• Ph.D. with 1+ years of industry experience OR Master's degree with 4+ years of industry experience.
• At least 1 year of experience directly related to healthcare ML/AI.
• Proven experience with multiple major product releases in a commercial SaaS environment.
• Proficiency in Python, SQL, and big data frameworks (e.g., Azure Data Lake, Apache Spark, or Databricks).
• Hands-on experience with transformer models, PEFT methods (LoRA, QLoRA), and Hugging Face Transformers.
• Experience deploying models using public cloud infrastructure (Azure, AWS, or GCP) with CI/CD pipelines.

Nice to have

• Proficiency in Java or other programming languages.
• Experience with reinforcement learning or RLHF.
• Knowledge of NLP techniques for summarization, extraction, or semantic search.
• Experience with retrieval-augmented generation (RAG) pipelines or agentic frameworks like LangChain and LlamaIndex.

Culture & Benefits

• Comprehensive benefits package starting from Day 1.
• Retirement plan matching.
• Flexible Paid Time Off.
• Wellness support programs and resources.
• Continuous development support program.
• Parental and caregiver leaves, and fertility/adoption support.