Johnson & Johnson currently has 73 active AI-related job listings. The majority of these roles, specifically 44%, are in the agents stage. Engineering is the most frequent function for these hires, followed by Product. The company is primarily hiring in the United States. Frequent tech tags include agent_orchestration and model_serving, suggesting a focus on AI system deployment and management. In the last 30 days, Johnson & Johnson posted 104 new AI roles, representing a significant increase of 420% compared to the previous 30-day period.
Currently tracking 49 active AI roles, down 53% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $77k–$283k (avg $144k).
Johnson & Johnson currently has 62 active AI-related roles in our index. The most common open titles are: Principal Scientist, Data Science - DDSAI - Therapeutics Development Supply (4), Data Scientist and Application Developer (2), Lead-Data Automation and Excellence (2), Postdoctoral Data Analytics Computational Sciences (2), Senior Program Manager, R&D (2). Most positions are in Engineering and Product.
Johnson & Johnson's active AI hiring is concentrated in: agents (40%), application (19%), data (18%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Johnson & Johnson is hiring AI talent in: United States (38 roles), Spain (7 roles), Belgium (5 roles), Japan (4 roles).
Job postings at Johnson & Johnson most frequently reference: agent orchestration, model serving, llm observability, fine tuning, rag.
In the past 30 days, Johnson & Johnson has posted 69 new AI-related roles. That is a -37% change versus the prior 30 days (109 → 69).
| Title | Stage | AI score |
|---|---|---|
| Postdoctoral Data Analytics Computational Sciences Postdoctoral researcher for application of advanced AI/ML methods to microscopic images of clinical and preclinical histopathology. Focus on application and refinement of deep learning algorithms to quantitate histopathology, and implementation of novel state-of-the-art techniques. Improve understanding of cellular organization and tissue structure to enhance clinical trial efficacy and efficiency. | Post-trainServe | 9 |
| Postdoctoral Data Analytics Computational Sciences Postdoctoral researcher focused on applying and refining deep learning algorithms for microscopic image analysis in histopathology, aiming to improve drug discovery and clinical trial efficacy. The role involves developing innovative computer vision solutions, collaborating with cross-functional teams, and contributing to scientific publications. |
| Post-train |
| 8 |
| Postdoctoral Researcher Video team Postdoctoral researcher to join the Video Understanding team, focusing on designing, implementing, and evaluating state-of-the-art AI/ML methods for frame-level and video-level understanding across diverse medical modalities. The role involves developing robust uncertainty models and multi-modal architectures to extract reliable insights from clinical data, collaborating with clinicians and engineers to translate algorithms into high-impact tools for clinical trial efficacy and workflows. | Post-trainAgent | 8 |
| Postdoctoral Researcher - AI in Digital Health Postdoctoral researcher focused on developing and validating AI/ML solutions for digital health, with expertise in speech analysis and NLP, to extract insights from multimodal data. | Post-trainData | 8 |
| Senior Scientist, Multiomic Therapeutics Senior Scientist role focused on computational biology and AI/ML model development for therapeutic discovery, specifically an AI-powered siRNA design and off-target prediction framework. Requires expertise in omics data analysis, AI/ML, and pipeline development. | Post-train | 8 |
| Senior Scientist, Multiomics Perturbation Senior Scientist role focused on applying advanced computational models and AI/ML to integrate multi-modal perturbation data and human omics datasets for target/pathway nomination in therapeutic discovery for immune-mediated diseases. The role involves developing predictive frameworks, identifying target combinations, and performing in silico target deconvolution to inform portfolio decisions. Requires expertise in AI/ML for biological datasets, prediction modeling, phenotype scoring, and multi-omics integration. | Post-train | 8 |
| Postdoctoral Scholar, AI/ML for drug metabolite prediction and LC-MS analytical chemistry This role focuses on developing and evaluating AI/ML models for drug metabolite prediction, pharmacokinetics, and molecular properties within a healthcare/drug discovery context. It involves fundamental research using internal datasets, developing explainable AI tools with uncertainty estimation and active learning, and publishing findings. The role is primarily research-oriented, building and evaluating deep learning methods for analytical instrumentation and drug discovery processes. | Post-train | 7 |
| Postdoc on cofolding models for In-Silico Drug Discovery Postdoctoral researcher focused on developing and fine-tuning co-folding models for in-silico drug discovery, involving dataset curation, model evaluation, and integration into discovery workflows within a healthcare/biotech domain. | Post-train | 7 |
| Principal Scientist – Data Science (RWE) Principal Scientist - Data Science (RWE) at Johnson & Johnson Innovative Medicine in Madrid, Spain. This role focuses on developing and deploying cutting-edge statistical/machine learning models using Real World Data (RWD) to gain insights into diseases, improve patient outcomes, and enhance clinical development. The position requires a Ph.D. or Master's degree in a quantitative field, extensive experience in statistical modeling or machine learning, and proficiency in Python/R and SQL. The role involves leading projects, collaborating with cross-functional teams, and mentoring junior scientists. | Post-train | 7 |
| Postdoctoral Scientist Data Science AI/ML & DH Postdoctoral Scientist role focused on developing digital biomarkers and AI/ML algorithms for digital endpoint development using wearable sensor data within Johnson & Johnson's Innovative Medicine Research & Development division. Responsibilities include data analysis, feature extraction, model building, pipeline development, and collaboration with cross-functional teams, with an emphasis on scientific publication. | Post-trainData | 7 |