Senior ML Engineer

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 Intelligen