Senior ML Engineer II

About this role

ABOUT THIS POSITION

We 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 DO Data 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.

ABOUT WAYSTAR

Through a smart platform and better experience, Waystar helps providers simplify healthcare payments and yield powerful results throughout the complete revenue cycle. Waystar’s healthcare payments platform combines innovative, cloud-based technology, robust data, and unparalleled client support to streamline workflows and improve financials so providers can focus on what matters most: their patients and communities. Waystar is trusted by 1M+ providers, 1K+ hospitals and health systems, and is connected to over 5K commercial and Medicaid/Medicare payers.  We are deeply committed to living out our organizational values: honesty; kindness; passion; curiosity; fanatical focus; best work, always; making it happen; and joyful, optimistic & fun.

Waystar products have won multiple Best in KLAS® or Category Leader awards since 2010 and earned multiple #1 rankings from Black Book™ surveys since 2012. The Waystar platform supports more than 500,000 providers, 1,000 health systems and hospitals, and 5,000 payers and health plans. For more information, visit waystar.com   or follow @Waystar   on Twitter.   

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 ho

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