Location: Palo Alto, CA (Hybrid)
Role Type: Full-Time / Permanent
Our client, a pioneering HealthTech AI company in Palo Alto, is seeking a high-calibre Applied AI Engineer to bridge the gap between advanced Machine Learning and robust Software Engineering. This is an end-to-end ownership role: you will be responsible for designing the logic, building the architecture, and deploying the final services.
Core Responsibilities
- Architect AI Workflows: Design and implement sophisticated agentic workflows and automation sequences that power clinical decision-making.
- System Design & Integration: Build the backend infrastructure, scalable REST APIs, and data services required to support high-concurrency AI applications.
- Rapid Deployment: Maintain a high-velocity shipping cycle, moving from prototype to production-grade implementation in days.
- Model Orchestration: Select, fine-tune, and evaluate the performance of various LLMs (including OpenAI, Anthropic, and open-source models) for specific healthcare tasks.
- Full-Stack ML: Own the pipeline from data ingestion and time-series forecasting to real-time classification and model monitoring.
- Computer Science Mastery: Expert knowledge of algorithms, data structures, and distributed systems.
- Software-Heavy Background: Professional-grade Python skills. You should be comfortable with software design patterns, testing, and CI/CD.
- Machine Learning Fundamentals: * Deep understanding of Core ML topics: classification, regression, and clustering.
- Specific experience in Time Series Forecasting and temporal data analysis.
- Proficiency in Generative AI: RAG architectures, prompt optimization, and agent frameworks.
- Infrastructure: Experience deploying services to cloud environments (GCP preferred) and a solid grasp of MLOps and pipeline automation.
- Education: BS in Computer Science or related field 4 years of experience, or an MS 2 years of experience.
- Startup Agility: You possess the "scrappiness" to solve problems with limited resources but the rigor to ensure those solutions are enterprise-grade.
- The "Generalist" Mindset: You enjoy working across the entire stack and are not afraid to dive into data engineering or infrastructure when needed.
- Mission-Oriented: You are motivated by the prospect of using AI to significantly improve healthcare
Please apply for more details