Principal AI Lead – Surgical AI

Johnson & Johnson Johnson & Johnson · Pharma · Santa Clara, CA +1

Principal AI Lead for the Polyphonic® Applied AI and ML team, focusing on building and deploying surgical AI models and agents. The role involves owning the full ML lifecycle, from research and development to scalable deployment, and creating platforms and user experiences for data scientists and developers. Key responsibilities include standardizing AI development pipelines, developing modular intelligence components, selecting and deploying various model families (CNN, transformer, LLM/VLM), integrating models with product functionality, optimizing inference, and bringing product judgment to MLOps platform development.

What you'd actually do

  1. Conceptualize structured pipelines (ingestion to production), planning flows, agentic workflows
  2. Build capability primitives such as pre-built models, feature stores, AI-assisted annotations, proactive insights
  3. Develop modular and reusable intelligence components
  4. Select appropriate model families based on capability and cost constraints
  5. Lead the design and deployment of CNN-based, transformer-based and LLM/VLM-based models

Skills

Required

  • MS or PhD in Machine Learning, Artificial Intelligence, Computer Science, or a related field
  • 10+ years of experience in machine learning engineering or applied AI, with significant ownership of production systems
  • Deep expertise in computer vision-based deep learning
  • Demonstrated experience developing and deploying production models on cloud and edge
  • Strong product competence for ML platforms/MLOps
  • Advanced proficiency in PyTorch and the modern ML ecosystem
  • Strong software engineering skills in Python and experience designing scalable ML systems
  • Proven track record to lead sophisticated technical initiatives and influence technical direction across teams
  • Excellent communication and teamwork skills

Nice to have

  • Experience building or working on ML or developer platforms for data scientists and researchers, including driving adoption through documentation, templates, and self-serve workflows
  • Familiarity with MLFlow, Kubeflow, or similar MLOps platforms
  • Experience developing AI systems in regulated environments (e.g., SaMD), such as surgical, medical imaging, or healthcare-related ML/AI applications, with attention to traceability, validation, and auditability
  • Experience with foundation models, multimodal AI, or vision-language architectures
  • Prior experience mentoring or leading ML engineering teams
  • Experience working with large-scale datasets or distributed training systems

What the JD emphasized

  • Deep expertise in computer vision-based deep learning
  • Demonstrated experience developing and deploying production models on cloud and edge
  • Strong product competence for ML platforms/MLOps
  • Advanced proficiency in PyTorch and the modern ML ecosystem
  • Strong software engineering skills in Python and experience designing scalable ML systems
  • Proven track record to lead sophisticated technical initiatives and influence technical direction across teams
  • Experience developing AI systems in regulated environments (e.g., SaMD), such as surgical, medical imaging, or healthcare-related ML/AI applications, with attention to traceability, validation, and auditability

Other signals

  • building the next generation intelligence infrastructure and platforms
  • shaping and defining core workflows for developing and deploying surgical AI models and agents
  • own and drive technical direction across the full ML lifecycle—from research and model development to scalable deployment
  • build the right platform and user experiences for data scientists and developers