Senior ML Engineer II

• 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.

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., + 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.

• 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

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 (https://twitter.com/Waystar) on Twitter.