Company Description
At MediScan AI, we’re building an AI-native workspace designed for physicians and legal teams to analyze and report on complex, disorganized patient histories. Our tools empower users to process vast amounts of medical data efficiently, enabling faster, more accurate decision-making.
As a team, we focus on blending cutting-edge AI technologies with intuitive, user-focused design to tackle one of the most underserved pain points in the healthcare industry. By joining MediScan AI, you’ll have the chance to work on meaningful challenges—building scalable solutions for messy, real-world problems—and make an immediate impact at a fast-growing startup.
We’re not just solving technical problems; we’re transforming how work gets done in healthcare, helping professionals unlock productivity and focus on what matters most.
Role Description
This is a full-time hybrid role for an AI Engineer at MediScan AI. The role is located in Seattle, WA with some work from home flexibility.
What You’ll Do
• Architect & scale AI-driven workflows, including autonomous agents that reason, retrieve, and act.
• Design and optimize AI infrastructure that supports real-time and batch processing at scale.
• Work across the stack— from ML models to distributed systems —to enable AI-driven decision-making.
• Collaborate closely with leadership and customers to ensure AI systems align with real-world user needs.
• Experiment with LLMs, retrieval-augmented generation (RAG), NLP, OCR, and reinforcement learning to push the boundaries of AI application layers.
Qualifications
Must-Haves:
• Experience building agentic AI systems —LLMs that autonomously plan, retrieve, and execute actions.
• Proven experience scaling AI infrastructure , including orchestration of models, vector databases, and inference pipelines.
• Strong engineering skills in TypeScript, Node.js, and Python , with an ability to ship production-grade AI applications.
• Experience deploying and fine-tuning LLMs, transformers, or multi-modal models .
• Deep problem-solving skills with a passion for building AI-driven products that solve real-world problems .
Nice-to-Haves:
•Experience with OCR, NLP, or document intelligence in production systems.
• Familiarity with LLM deployment best practices , fine-tuning techniques, and retrieval-augmented generation (RAG).
• DevOps and MLOps experience , including infrastructure-as-code (AWS CDK, Terraform), container orchestration (Kubernetes, ECS), and GPU optimization.
• Background in healthcare, legal tech, or regulatory-heavy industries .
What We Offer
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