Director, Physical AI for Autonomous Discovery
Johnson & Johnson is hiring a Director, Physical AI for Autonomous Discovery. It pays $164k-$283k a year and Level rates it ; you can apply on Level.
Level's read on this job
- Builds AI ●●●● is how Level rates this role: the job is building AI systems.
- The posting mentions MLOps among its tools and skills.
- Level classes it as an executive role.
- Johnson & Johnson has 2,000+ other open roles on Level.
- This posting went up in the last few days.
AI in this role
At Johnson & Johnson, we believe health is everything. Our strength in healthcare innovation empowers us to build a world where complex diseases are prevented, treated, and cured, where treatments are smarter and less invasive, and solutions are personal. Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity. Learn more at jnj.com.
As guided by Our Credo, Johnson & Johnson is responsible to our employees who work with us throughout the world. We provide an inclusive work environment where each person is considered as an individual. At Johnson & Johnson, we respect the diversity and dignity of our employees and recognize their merit.
Job Function:
Data Analytics & Computational SciencesJob Sub Function:
Data ScienceJob Category:
People LeaderAll Job Posting Locations:
Cambridge, Massachusetts, United States of America, Spring House, Pennsylvania, United States of AmericaJob Description:
Our expertise in Innovative Medicine is informed and inspired by patients, whose insights fuel our science-based advancements. Visionaries like you work on teams that save lives by developing the medicines of tomorrow.
Join us in developing treatments, finding cures, and pioneering the path from lab to life while championing patients every step of the way.
Learn more at https://www.jnj.com/innovative-medicine
Johnson & Johnson Innovative Medicine is recruiting for a Director, Physical AI for Autonomous Discovery to join our In Silico Drug Discovery team. The preferred location for this position is Spring House, PA (Philadelphia area) and may require travel as needed. Consideration may be given for candidates near the Cambridge, MA area. (No remote option.)
Role Summary
The Director, Physical AI for Autonomous Discovery is a key leader who will define the Physical AI strategy and lead a focused team developing models that enable autonomous laboratory experimentation. This role combines AI, robotics, laboratory automation, and scientific reasoning to create systems that perceive, reason, act, learn, recover from errors, and continuously improve experimental outcomes.
Key Responsibilities
- Define and execute the Physical AI strategy, build and lead a high-performing team, and establish a roadmap aligned with scientific priorities and business objectives.
- Develop AI models that understand and reason about instruments, samples, reagents, robotic systems, workflows, and laboratory state.
- Build adaptive experimental optimization capabilities using active learning, Bayesian optimization, reinforcement learning, and multi-objective optimization.
- Create systems for physical error detection and correction, including anomaly recognition, root-cause assessment, workflow replanning, recovery actions, and appropriate human escalation.
- Develop models that generate hypotheses for experimental failures, unexpected results, variability, and irreproducibility, and recommend discriminating follow-up experiments.
- Design agentic and multi-agent systems that coordinate experiment planning, execution monitoring, data interpretation, and decision-making across Design-Make-Test-Analyze cycles.
- Partner with automation, robotics, data science, engineering, and discovery scientists to deploy reliable closed-loop learning in real laboratory environments.
- Embed calibrated uncertainty, safety constraints, monitoring, traceability, and governance into autonomous decision-making.
What Success Looks Like
- Laboratory systems detect, diagnose, and recover from execution failures with fewer unplanned interventions.
- AI-generated hypotheses explain experimental anomalies and guide informative follow-up experiments.
- Closed-loop optimization improves experimental quality, throughput, reproducibility, and scientific decision-making.
- Autonomous capabilities progress safely from AI-assisted automation to self-improving discovery workflows.
- Work closely with J&J IT and Data, Data Science & AI partners to deliver a robust and secure agentic platform.
Key Skills
Physical AI & World Models
Embodied AI, multimodal perception, state estimation, digital twins, and predictive models of laboratory systems.
Autonomous Experimentation
Active learning, Bayesian optimization, sequential design, reinforcement learning, and multi-objective optimization.
Error Intelligence
Anomaly detection, fault diagnosis, causal reasoning, hypothesis generation, recovery planning, and uncertainty quantification.
Robotics & Automation
Laboratory robotics, liquid handling, sensors, machine vision, orchestration, scheduling, and instrument integration.
Agentic AI
Scientific agents, multi-agent coordination, planning, tool use, memory, guardrails, and human-on-the-loop controls.
Scientific Software
Python and modern AI/ML frameworks; production model deployment, APIs, data pipelines, observability, and MLOps.
Qualifications
- PhD in artificial intelligence, machine learning, robotics, computer science, engineering, computational biology, or a related quantitative field.
- Demonstrated experience developing AI systems that operate in physical or scientific environments.
- Deep expertise in several relevant areas, such as world models, reinforcement learning, Bayesian optimization, causal inference, multimodal AI, robotics, or scientific machine learning.
- Strong software-development skills, including Python and modern machine-learning frameworks.
- Ability to translate scientific and operational requirements into robust, scalable AI models and to communicate across multidisciplinary teams.
- Strong collaboration skills to work in matrix environment.
Preferred Experience
- Self-driving laboratories, laboratory automation, or closed-loop scientific experimentation.
- Vision-language-action models, digital twins, machine vision, robotic control, or multi-agent systems.
- Biologics, drug discovery, life sciences, or another complex experimental domain.
- Deployment of safety-critical or high-reliability AI systems with monitoring and governance controls.
The preferred location for this position is Spring House, PA (Philadelphia area) and may require travel as needed. Consideration may be given for candidates near the Cambridge, MA area. (No remote option.)
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.
If you are under 18 years of age, you (the candidate) may need to obtain the necessary working papers or other documentation required by state law to start the assignment, as well as get a parent’s consent for the background check.
Johnson & 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, external applicants please contact us via https://www.jnj.com/contact-us/careers , internal employees contact AskGS to be directed to your accommodation resource.
The anticipated base pay range for this position is $164,000 to $282,900. The Company maintains highly competitive, performance-based compensation programs. Under current guidelines, this position is eligible for an annual performance bonus in accordance with the terms of the applicable plan. The annual performance bonus is a cash bonus intended to provide an incentive to achieve annual targeted results by rewarding for individual and the corporation’s performance over a calendar/performance year. Bonuses are awarded at the Company’s discretion on an individual basis. Employees and/or eligible dependents may be eligible to participate in the following Company sponsored employee benefit programs: medical, dental, vision, life insurance, short- and long-term disability, business accident insurance, and group legal insurance.
Employees may be eligible to participate in the Company’s consolidated retirement plan (pension) and savings plan (401(k)).
Employees are eligible for the following time off benefits:
Vacation – up to 120 hours per calendar year
Sick time - up to 40 hours per calendar year
Holiday pay, including Floating Holidays – up to 13 days per calendar year of Work, Personal and Family Time - up to 40 hours per calendar year
Additional information can be found through the link below. https://www.careers.jnj.com/employee-benefits
The compensation and benefits information set forth in this posting applies to candidates hired in the United States. Candidates hired outside the United States will be eligible for compensation and benefits in accordance with their local market.
#LI-SL
#JNJDataScience
#JNJIMRND-DS
#JRDDS
#LI-Hyrbid
Required Skills:
Preferred Skills:
Advanced Analytics, Budget Management, Compliance Management, Critical Thinking, Data Analysis, Data Privacy Standards, Data Quality, Data Reporting, Data Savvy, Data Science, Data Visualization, Developing Others, Digital Fluency, Inclusive Leadership, Leadership, Program Management, Strategic Thinking, Succession PlanningHow we rate this
Director, Physical AI for Autonomous Discovery at Johnson & Johnson rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- How do you monitor a model once it's live, and how do you know it needs retraining?
- How would you decide a model or AI system is ready to ship?
- Tell me about a time a model underperformed in production. How did you find out, and what did you change?
Adapt your resume
- List these exact terms on your resume: ML Ops. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
Want an expert to read your CV for this job?
Free. Send your CV and the role you want next. We reply by email within 2 to 4 business days.
Get new AI jobs (Builds AI ●●●●) by email
One email a week with the new AI jobs (Builds AI ●●●●), each rated for how much AI is in the work. No recruiter spam, unsubscribe in one click.
Free. One email a week. Unsubscribe in one click.
Similar roles
Other roles that build AI, at other companies.
What kind of AI work fits you?
Answer 12 practical questions in about three minutes. Get a simple profile, the work it points to, and live roles to explore next.
Find my next step