This role pays less than
88%
of similar roles. Most pay
$195,150–$266,000
— the shaded band above.
At the midpoint, this role pays about
$159k
versus about
$231k
for comparable roles.
Based on 240 similar postings.
Employer
About Johnson & Johnson
Johnson & Johnson is a multinational corporation operating in three main segments: consumer health products, pharmaceuticals, and medical devices, known for brands like Tylenol, Band-Aid, and Janssen. Industry: Pharmaceuticals & Medical Devices
Johnson & Johnson currently has
46 open roles
on FindRole.
Listed pay typically runs
$117,000–$201,250
across 42 roles with salary data.
Principal Scientist, AI & Autonomous Discovery Systems joins the Data, Data Science, and AI team to advance drug discovery through human-guided autonomous and agentic platforms. This technical leadership role focuses on building Design-Make-Test-Learn ecosystems that integrate models, data, experiments, and laboratory automation to improve decision quality and increase experimental throughput across various therapeutic areas. The successful candidate will develop multi-agent architectures for laboratory orchestration, connect diverse systems like robotics and cloud services into coherent workflows, and establish standards for AI governance and safety. Required expertise includes advanced AI/ML, generative AI, foundation models, and multimodal AI using Python with frameworks like PyTorch, TensorFlow, or JAX. The role addresses the complex challenge of accelerating high-value therapeutic programs by creating intelligent systems that automate research cycles and integrate scientific literature and predictive models into discovery processes.
Build AI-enabled discovery workflows connecting target discovery, molecular design, experiment planning, and data interpretation across multiple modalities.
Define the technical vision and multi-agent architecture for human-guided autonomous discovery systems and laboratory orchestration.
Integrate AI models, robotics, and cloud services into coherent Design-Make-Test-Learn workflows that learn from experimental outcomes.
Develop intelligent scientific systems using multimodal AI models to advance hypothesis generation and automated decision-making.
Establish rigorous standards for AI governance, safety, reliability, and data security in production environments.
Partner with cross-functional teams of scientists and engineers to deliver production-grade AI capabilities for drug discovery.
Mentor staff and communicate technical strategies through internal presentations, publications, patents, and conference participation.
What we're looking for
Ph.D. in Biomedical/Electrical/Chemical Engineering, Computer Science, Machine Learning, Computational Biology, Bioinformatics, Computational Chemistry, or a related quantitative discipline.
At least 3 years of post-graduate experience applying advanced AI/ML technologies in scientific, pharmaceutical, biotechnology, healthcare, or industrial research settings.
Strong expertise in agentic AI, scientific computing, modern software engineering, generative AI, foundation models, and multimodal AI.
Proficiency in Python and frameworks such as PyTorch, TensorFlow, JAX, or equivalent platforms.
Demonstrated ability to architect enterprise-scale AI platforms, scientific software systems, or production-grade AI applications.
Experience with drug discovery or clinical development and the ability to partner effectively with domain scientists and experimental teams.
Excellent written and verbal communication skills for collaboration in a matrixed organization.
Experience designing human-guided autonomous workflows involving laboratory automation, robotics, and cloud infrastructure (preferred); experience with analytical instrumentation like LC/MS or NMR (preferred).