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.