CAREERS

AI & Data Platform Architect

Posted on - 15 Jul 2025

About Us

We’re a health-tech startup using AI and data to accelerate drug discovery and improve patient care. Our platform combines clinical, genomic, and biological data with advanced AI models like LLMs and multimodal deep learning to unlock new insights in human health.

Role Summary
We’re looking for a hands-on AI & Data Platform Architect to design and build a scalable, secure, and modular platform that powers AI research in healthcare. You’ll lead the technical architecture for training and deploying models on complex biomedical data, helping shape the future of AI in life sciences.

Key Responsibilities

  • Design and build a scalable AI/ML platform to support data pipelines, model training, and deployment.
  • Work with large, diverse biomedical datasets (clinical, genomic, proteomic, chemical).
  • Build secure, cloud-native infrastructure using containers and APIs.
  • Implement and scale foundation models, knowledge graphs, and embeddings.
  • Ensure compliance with security and privacy standards (e.g., HIPAA, SOC2).
  • Collaborate with cross-functional teams (data scientists, clinicians, engineers).
  • Mentor engineers and set best practices for ML platforms and MLOps.

Required Skills & Experience

  • Master’s or PhD in Computer Science, AI/ML, or related field.
  • 10+ years in AI platform or infrastructure roles.
  • Strong experience with Python, ML frameworks (PyTorch, TensorFlow), and cloud platforms (AWS, GCP, Azure).
  • Experience with distributed systems, MLOps, and tools like MLFlow, Kubeflow, Databricks.
  • Familiar with GPUs, performance optimization, and data security practices.

Nice to Have

  • Background in life sciences or biomedical data (genomics, proteomics, EHRs).
  • Familiarity with drug discovery workflows and generative AI tools like LangChain or Hugging Face.
  • Knowledge of bioinformatics databases and ontologies.

What We Offer

  • Chance to shape a cutting-edge AI platform in a mission-driven startup.
  • Equity and growth opportunities in a fast-moving team.
  • Budget for learning and experimentation with AI/cloud tools.