ABOUT THIS POSITIONWe are seeking a highly skilled and innovative Senior ML Engineer with a passion for building robust, efficient, and domain-specific AI systems using Language Models (LMs) and agentic architectures. As a core member of the team, you will be instrumental in developing the entire ML pipeline, from sophisticated data extraction techniques to fine-tuning specialized LMs and orchestrating their interactions within a multi-agent framework.
This is a unique opportunity to apply state-of-the-art Generative AI and NLP techniques to a real-world, high-impact problem, leveraging the latest research in agentic AI and LMs to deliver economical and powerful solutions.
WHAT YOU'LL DOData Pipeline & Knowledge Base Construction:- Design, implement, and optimize robust pipelines for ingesting, parsing, and extracting structured information from complex documents (leveraging OCR, document layout analysis, Named Entity Recognition (NER), and Relationship Extraction (RE).
- Develop rich, nested JSON schemas for representing structured data and ensure scalable storage
- Generate and manage high-quality vector embeddings for efficient retrieval-augmented generation (RAG) within a Vector Database.
Language Model (LM) Development & Fine-tuning:- Research, select, and experiment with appropriate open-source Language Models (Large & Small) (e.g., Phi-3, Mistral, Llama, Nemotron-H families) for specialized tasks.
- Design and execute efficient fine-tuning strategies (e.g., LoRA, QLoRA, full fine-tuning) on curated, domain-specific datasets to achieve precise performance for tasks like coverage determination, code lookups, and policy rule application.
- Explore and implement knowledge distillation techniques to transfer capabilities from larger models to smaller, more efficient LMs.
Agentic System Design & Implementation:- Build and maintain the core agentic framework, including the orchestrator that intelligently routes queries and coordinates interactions between various specialized LM tools.
- Develop and integrate "tools" (specialized LMs and external APIs) that perform atomic medical necessity tasks, ensuring strict behavioral alignment and structured outputs.
MLOps & Deployment:- Deploy, manage, and monitor LMs and agentic components on Google Cloud Platform (GCP) using services like Vertex AI, GKE, Cloud Functions, and Cloud Run.
- Implement robust MLOps practices for continuous integration, continuous delivery (CI/CD), model versioning, and performance monitoring (latency, throughput, accuracy).
Continuous Improvement & Research:- Establish effective feedback loops from end-user interactions and system logs to identify areas for model improvement.
- Curate and expand training datasets, ensuring data privacy (PHI/PII masking) and legal compliance.
- Stay abreast of the latest research in LMs, agentic AI, NLP, and document understanding, applying relevant advancements to our system.
Collaboration:- Work closely with subject matter experts, product managers, and other engineers to translate complex requirements into technical solutions and evaluate system performance.
WHAT YOU'LL NEED- Bachelor's or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, Statistics, or a related quantitative field. Ph.D. preferred.
- 5+ years of professional experience in machine learning engineering, with a strong track record of deploying and maintaining ML models in production environments.
- Expertise in programming languages such as Python (with extensive experience in ML libraries like TensorFlow, PyTorch, Scikit-learn).
- Deep understanding of machine learning fundamentals, including supervised, unsupervised, and reinforcement learning techniques, as well as deep learning architectures.
- Strong experience with cloud platforms (AWS, Azure, GCP) and their ML services.
- Proficiency in building and managing data pipelines using tools like Spark, Kafka, SQL, and NoSQL databases.
- Demonstrated experience with MLOps principles and tools (e.g., MLflow, Kubeflow, Sagemaker, Airflow).
- Excellent problem-solving skills and the ability to work independently on complex issues.
- Strong communication and interpersonal skills, with the ability to collaborate effectively in a cross-functional team.
- Experience in the healthcare technology domain is a significant plus.
- Proven ability to lead technical initiatives and influence architectural decisions.
WAYSTAR PERKS- Competitive total rewards (base salary + bonus, if applicable)
- Customizable benefits package (3 medical plans with Health Saving Account company match)
- We offer generous paid time off for our non-exempt team members, starting with 3 weeks + 13 paid holidays, including 2 personal floating holidays. We also offer flexible time off for our exempt team members + 13 paid holidays
- Paid parental leave (including maternity + paternity leave)
- Education assistance opportunities and free LinkedIn Learning access
- Free mental health and family planning programs, including adoption assistance and fertility support
- 401(K) program with company match
- Pet insurance
- Employee resource groups
