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Overview

Johnson & Johnson MedTech is focused on shaping the future of digital surgery and expanding its robotics and digital solutions offerings across the entire portfolio with multi-specialty end-to-end solutions in endoluminal intervention general surgery and a comprehensive digital portfolio. This includes the Polyphonic platform a first-of-its-kind digital platform that advances patient empowerment surgical performance operating room (OR) collaboration and operational efficiency by synchronizing devices data and AI driven insights in one place to simplify access build confidence and unify a non-linear care experience.

We are recruiting for a Principal AI Lead within the Polyphonic Applied AI and ML team located in Santa Clara CA. J&J is building the next generation intelligence infrastructure and platforms to capture extract and apply intelligence from the OR and surgical workflows and this role will play a key role in shaping and defining core workflows for developing and deploying surgical AI models and agents for the clinical consumption.

This is an opportunity to work with a multi-functional high-value team of product managers applied scientists software engineers and clinical experts who will push the boundaries for surgical AI and make it widely accessible. The candidate will own and drive technical direction across the full ML lifecyclefrom research and model development to scalable deployment bringing both deep technical expertise and strong product acuity to build the right platform and user experiences for data scientists and developers while mentoring engineers and partnering closely with product engineering and clinical domain experts.

What You Will Do

AI Development Standardization

• Conceptualize structured pipelines (ingestion to production) planning flows agentic workflows

• Build capability primitives such as pre-built models feature stores AI-assisted annotations proactive insights

• Develop modular and reusable intelligence components

Applied AI/ML Features & Model Strategy

• Select appropriate model families based on capability and cost constraints

• Lead the design and deployment of CNN-based transformer-based and LLM/VLM-based models

• Apply prompting constraints and reasoning structures to reduce hallucination

Model Integration & Inference Optimization

• Integrate sophisticated models with product functionality and ensure output reliability consistency safety and user-centric alignment

• Develop logic for hybrid model usage

• Collaborate with engineering to optimize latency cost and scalability

Product Acuity

• Bring strong product judgement to the development of the MLOps platform balancing researcher/data scientist workflows with engineering security and compliance constraints.

• Partner with multi-functional collaborators to define user needs success metrics and a prioritized roadmap for platform capabilities.

• Make pragmatic tradeoffs across build vs. buy usability vs. flexibility and time-to-value vs. long-term scalability for ML platform components.

Required Qualifications

• 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 (or equivalent experience).

• 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 with the ability to translate multi-functional needs into a clear roadmap and excellent developer/researcher experiences.

• 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.

Preferred Qualifications

• 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.

Johnson & Johnson is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race color religion sex sexual orientation gender identity age national origin disability protected veteran status or other characteristics protected by federal state or local law. We actively seek qualified candidates who are protected veterans and individuals with disabilities as defined under VEVRAA and Section 503 of the Rehabilitation Act.

Johnson and Johnson is committed to providing an interview process that is inclusive of our applicants needs. If you are an individual with a disability and would like to request an accommodation please email the Employee Health Support Center () or contact AskGS to be directed to your accommodation resource.

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