Senior ML Engineer

About this role

ABOUT THIS POSITION

Job Description Summary

We are seeking a highly skilled and innovative Machine Learning 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.  

• Bachelor's or Master's degree in Computer Science , Machine Learning, Artificial Intelligence, or a related quantitative field.  

• 3+ years of professional experience in Machine Learning Engineering, with a strong focus on NLP.  

• Proven experience with Language Models (LMs), including model selection, fine-tuning, and deployment.  

• Strong proficiency in Python and familiarity with ML frameworks (e.g., PyTorch , TensorFlow, Hugging Face Transformers).  

• Solid understanding and hands-on experience with core NLP techniques and architectures, especially Transformers.  

• Experience with cloud platforms, particularly Google Cloud Platform (GCP), including services like Vertex AI, Cloud Storage, and compute services.  

• Familiarity with MLOps principles and tools for model serving, monitoring, and pipeline automation.  

• Excellent problem-solving skills, attention to detail, and ability to work independently and collaboratively.  

• Active use of artificial intelligence (AI) tools and techniques to enhance performance, drive innovation, and improve decision-making across business functions.  

• Ability to leverage AI tools and platforms to streamline workflows, improve decision-making, and drive innovation.  

• Curiosity and adaptability in exploring emerging AI technologies, with a mindset for continuous learning and experimentation.  

WHAT YOU'LL NEED • What Will Make You Stand Out (Preferred Qualifications):  

• Hands-on experience building or contributing to agentic AI systems or multi-agent frameworks.  

• Direct experience with document processing technologies such as OCR, layout parsing, Document AI, or custom information extraction from unstructured text.  

• Experience with Vector Databases (e.g., pgvector , Pinecone, Weaviate , Qdrant ) and RAG architectures.  

• Exposure to the healthcare domain, particularly understanding medical terminology, CPT/ICD codes, or regulatory documents.  

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 multipl

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