AI Application Engineer

Human Longevity, founded by one of the leading scientists of the 21 st century, Dr. Craig Venter, is at the forefront of revolutionizing preventative care and advancing the practice of medicine. Our clinic integrates cutting-edge technology with personalized healthcare solutions to promote healthy aging and 100+ living. Join us in our mission to transform the future of medicine! Role Description We are seeking a technical AI Application Engineer to architect, build, and deploy AI systems into production at scale. This role focuses on the engineering backbone of applied AI - from infrastructure, pipelines, and APIs, to fine-tuning and serving large models. You will work across LLMs, multimodal ML, and automation systems to enable real-world healthcare applications. Responsibilities End-to-End AI Development : Design, implement, and maintain ML/LLM pipelines, from data preprocessing and model training to deployment and monitoring. Infrastructure Engineering : Build and optimize scalable, cloud-native AI services (AWS/GCP/Azure, Docker, Kubernetes, Ray, MLflow, Weights & Biases). Model Deployment & Serving : Develop APIs and microservices to deliver AI/ML models in production with low latency and high reliability. LLM & NLP Engineering : Fine-tune, prompt-engineer, and optimize large language models for clinical text, structured data integration, and workflow automation. Multimodal AI : Integrate genomics, imaging, and longitudinal health data into multimodal ML pipelines. Data Engineering : Architect robust ETL pipelines for large-scale structured/unstructured data (e.g., genomics, EHR, imaging, wearable data). Observability & MLOps : Implement monitoring, versioning, testing, and continuous delivery of ML systems. Security & Compliance : Ensure systems meet HIPAA, GDPR, and other healthcare regulatory requirements. Collaboration : Partner with clinical, product, and data science teams to translate R&D prototypes into production-grade applications. Qualifications Bachelor’s or Master’s in Computer Science, Engineering, or related field (PhD a plus). 4+ years of experience in applied machine learning, data engineering, or AI systems engineering. Proficiency in Python and frameworks such as PyTorch, TensorFlow, JAX, Hugging Face. Experience deploying ML models into production at scale (REST APIs, gRPC, batch/stream processing). Strong background in distributed systems and cloud-native architectures (AWS SageMaker, GCP Vertex AI, Azure ML, or equivalent). Experience with LLMs/NLP and familiarity with fine-tuning, retrieval-augmented generation (RAG), and embedding-based search. Knowledge of multimodal ML (text, image, genomics, or medical data) is a strong plus. Familiarity with MLOps toolchains (e.g., MLflow, Kubeflow, Airflow, Prefect, Weights & Biases). Experience with containerization and orchestration (Docker, Kubernetes). Bonus: Exposure to healthcare/biotech data (EHR/EMR, genomics, PACS/DICOM imaging). What We offer Build cutting-edge AI systems applied to genomics, multi-omics, and precision medicine. Work with a team of world-class scientists, engineers, and clinicians. Competitive compensation and stock options. Comprehensive health, wellness, and longevity benefits. Seniority level

Seniority level Mid-Senior level Employment type

Employment type Full-time Job function

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