Senior ML Engineer

Waystar, Inc; Atlanta (GA); On-site; USD 100,000 - 160,000; Full time

Benefits offered by this job

Competitive base salary with bonus potential

Customizable benefits package

Generous paid time off

Paid parental leave

Education assistance

401(k) program with company match

Pet insurance

Job summary

Waystar, Inc in Atlanta, Georgia is seeking a highly skilled Machine Learning Engineer to develop end-to-end ML pipelines, fine-tune language models, and deploy solutions on Google Cloud Platform.

The role involves designing data pipelines, collaborating with experts to translate requirements into solutions, and implementing MLOps practices. The ideal candidate will have a strong background in NLP and hands-on experience with frameworks like PyTorch and TensorFlow.

Qualifications

• 3+ years of professional experience in Machine Learning Engineering with a focus on NLP.
• Proven experience with language model selection and deployment.
• Solid experience with core NLP techniques and transformer architectures.

Responsibilities

• Design and optimize data pipelines for ingesting and extracting information.
• Develop and manage vector embeddings for retrieval-augmented generation.
• Deploy and manage LMs on Google Cloud Platform.

Skills

Machine Learning Engineering

Natural Language Processing (NLP)

Python

Google Cloud Platform

MLOps

Education

Bachelor’s or Master’s degree in Computer Science or related field

Tools

PyTorch

TensorFlow

Hugging Face Transformers

Job description

Job Summary

We are seeking a highly skilled and innovative Machine Learning Engineer to develop end‑to‑end ML pipelines, fine‑tune language models, design agentic architectures, and deploy solutions on Google Cloud Platform.

Responsibilities

• Design and optimize data pipelines for ingesting, parsing, and extracting structured information from complex documents using OCR, layout analysis, NER, and relationship extraction.
• Develop nested JSON schemas and store scalable structured data.
• Generate and manage vector embeddings for retrieval‑augmented generation in a vector database.
• Research and select open‑source language models (e.g., Phi‑3, Mistral, Llama, Nemotron‑H) for domain tasks and experiment with fine‑tuning strategies such as LoRA, QLoRA, or full fine‑tuning.
• Implement knowledge distillation to transfer capabilities from large to smaller models.
• Build and maintain the core agentic framework, including an orchestrator that routes queries and coordinates interactions between specialized LM tools.
• Develop “tools” (specialized LMs or external APIs) that perform atomic medical‑necessity tasks and produce structured outputs.
• Deploy, manage, and monitor LMs and agentic components on Google Cloud Platform using Vertex AI, GKE, Cloud Functions, and Cloud Run.
• Implement MLOps practices for CI/CD, model versioning, and performance monitoring.
• Establish feedback loops from user interactions and logs to improve models and expand training data while ensuring PHI/PII masking and legal compliance.
• Stay current with research in language models, agentic AI, NLP, and document understanding.
• Collaborate with subject‑matter experts, product managers, and engineers to translate requirements into technical solutions and evaluate system performance.

Qualifications

• 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 model selection, fine‑tuning, and deployment.
• Strong proficiency in Python and familiarity with ML frameworks such as PyTorch, TensorFlow, and Hugging Face Transformers.
• Solid hands‑on experience with core NLP techniques and transformer architectures.
• Experience with cloud platforms, especially Google Cloud Platform, including 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 AI tools to enhance performance, drive innovation, and improve decision‑making.
• Curiosity and adaptability to explore emerging AI technologies.

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 extraction from unstructured text.
• Experience with vector databases (e.g., pgvector, Pinecone, Weaviate, Qdrant) and retrieval‑augmented generation architectures.
• Exposure to the healthcare domain and familiarity with medical terminology, CPT/ICD codes, or regulatory documents.

Benefits

• Competitive base salary with bonus potential.
• Customizable benefits package, including 3 medical plans and a Health Savings Account with company match.
• Generous paid time off: 3 weeks plus 13 paid holidays and 2 floating personal holidays for non‑exempt employees; flexible time off for exempt employees.
• Paid parental leave, including maternity and paternity leave.
• Education assistance, free LinkedIn Learning access, and mental health and family planning programs.
• 401(k) program with company match.
• Pet insurance.
• Employee resource groups.

Equal Opportunity Employer

Waystar is an equal‑opportunity workplace. Qualified applicants will receive consideration for employment regardless of race, color, religion, age, sex, national origin, disability status, genetics, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected under federal, state, or local laws. This applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, transfer, leaves of absence, compensation, and training.