Software Engineer, Machine Learning

About Super Dial

Super Dial is transforming healthcare with AI-powered solutions that optimize revenue cycle management. Our mission is to bring the power of large language models (LLMs) into mission-critical healthcare workflows, making them reliable, secure, and cost-efficient at scale.

We’re a fast-growing team at the intersection of AI, healthcare, and enterprise SaaS
, building systems that go beyond demos to deliver real-world impact for providers, patients, and payers.

We’re seeking a Staff Software Engineer, Machine Learning to build and scale the backend systems that power LLM applications in healthcare. This is a technical leadership role for someone excited to architect APIs, pipelines, and infrastructure that operationalize LLMs in a regulated, high-stakes industry. You’ll partner closely with product, ML engineers, and healthcare experts to translate workflows into robust, production-ready systems.

• Backend for LLMs
  :
  Architect and implement scalable, low-latency APIs and services that wrap and optimize LLMs for healthcare use cases.
• Data & Retrieval Pipelines
  :
  Build ingestion, preprocessing, and RAG pipelines to ground LLMs in clinical and revenue‑cycle data.
• LLMOps & Observability
  :
  Design monitoring, evaluation, cost tracking, and guardrails for reliability and responsible AI use.
• Performance & Optimization
  :
  Engineer solutions for caching, batching, load balancing, and scaling workloads in cloud and containerized environments.
• Security & Compliance
  :
  Implement HIPAA‑ready infrastructure with strong data governance and auditability.
• Cross‑Functional Collaboration
  :
  Work with product and domain experts to map business workflows into backend systems.
• Technical Leadership
  :
  Drive best practices, mentor peers, and influence the technical direction of LLM infrastructure.

• 5+ years of backend or full‑stack software engineering, with 3+ years on ML/LLM‑enabled applications.
• Strong coding skills in Python (plus one statically typed language such as Go, Java, or Type Script).
• Experience with LLM frameworks (Hugging Face, Lang Chain, Llama Index, OpenAI APIs, Anthropic, etc.).
• Deep knowledge of distributed systems, service‑oriented architecture, and API design.
• Cloud‑native expertise with AWS/GCP/Azure, Kubernetes, Docker, Terraform
  .
• Familiarity with MLOps/LLMOps: CI/CD for models, evaluation harnesses, monitoring, reproducibility.
• Excellent system design skills and ability to align architecture with product goals.

• Experience applying LLMs in healthcare or regulated industries (FHIR, HL7, HIPAA).
• Hands‑on experience with RAG pipelines, vector databases, structured‑output orchestration.
• Background in enterprise SaaS or mission‑critical platforms.
• Knowledge of responsible AI and privacy‑preserving ML techniques.

• Impact
  :
  Apply cutting‑edge AI to one of the most important industries in the world.
• Leadership
  :
  Take ownership over core ML/LLM systems and shape technical direction.
• Growth
  :
  Join a fast‑moving team where your work directly powers mission‑critical applications.
• Compensation
  :
  Competitive base salary ($145K–$250K), equity, and comprehensive health, dental, and vision coverage.

This role is on‑site in San Mateo, CA
.

If you’re excited to push LLMs beyond demos and into mission‑critical healthcare workflows
, we’d love to hear from you. Apply now and help shape the future of AI in healthcare.