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About 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 https://www.jnj.com
Job Function:
Data Analytics & Computational Sciences
Job Sub Function:
Multi-Family Data Analytics & Computational Sciences
Job Category:
Professional
All Job Posting Locations:
Cambridge, Massachusetts, United States of America, San Diego, California, United States of America, Spring House, Pennsylvania, United States of America, Titusville, New Jersey, United States of America
Job 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.
Our Immunology team leads in the development of transformational medicines for immunological disorders and illnesses. You can influence where medicine is going by restoring health to millions of people living with immune diseases.
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 and Johnson Innovative Medicine Research & Development LLC, a Johnson & Johnson company, is recruiting for a Director, R&D Data Science and Digital Health (DSDH) Immunology. The Director will report to the Executive Director, R&D Data Science and Digital Health Immunology. The primary and preferred location for this position is San Diego, CA. Consideration may be given for candidates who are or can be located near Spring House, PA; Titusville, NJ; or Cambridge.
Position Summary:
- Contribute to the design and execution of a Data Science & Digital Health (DSDH) Computer Vision and Digital Health (CVDH) strategy in alignment to the Immunology Therapeutic Area (IMM TA) goals and objectives
- Partner with DSDH colleagues and the IMM TA to define and prioritize a portfolio of innovative medicines in development in alignment with the IMM TA strategy
To successfully meet these objectives, this individual will work closely with individual clinical project teams as well as functional area partners in Translational Science, Translational Medicine, Discovery, Late Development, Market Access, Medical Affairs and other relevant functions.
Responsibilities
- Provide strategic input into the Immunology R&D DSDH CVDH priorities ranging from individual projects to large collaborations with internal functional areas and external institutions
- Work closely with the broader Data Science and Digital Health (DSDH) team and Immunology Therapeutic Area (TA) / Function Data Science teams to execute on critical data science initiatives (focused on computer vision-based endpoints and digital health solutions) to support delivery of the short and long-term J&J Innovative Medicine R&D Data Science and Digital Health strategy
- Collaborate with Immunology TA and functions in J&J Innovative Medicine R&D, the DSDH Insights & Analytics team, and DSDH Data Platform teams to conceive, develop, and execute on data science use-cases, build a roadmap to deliver the use-cases, from test and learn to scale up deployment
- Develop a deep understanding of the imaging and digital health data, technical solutions and partner ecosystem, align R&D data science use cases with the key data sets and partners (internal and external)
- Champion, build and drive large strategic and sophisticated DSDH projects to achieve the intended impact in a timely manner
- Perform detailed analyses, develop high quality materials, and communicate in critical executive forums to facilitate leadership decision making
- Other ad hoc responsibilities in support of the DSDH team’s objectives and overall R&D objectives, as required
Required Qualifications:
- MD, and/or PhD and/or Master’s degree in data science, computer science, bioinformatics, biomedical engineering or applied mathematics; experience in in data science, bioinformatics, computer science
- 6+ years of progressive professional experience in clinical/academic environment, pharmaceutical R&D, data science, computer vision, digital health, including life sciences companies, consulting firms with established healthcare Data Science and life sciences practices, and other companies in the data science ecosystem
- Consistent track record of collaboration and leading in a matrix organization, entrepreneurial skill, and ability to influence and engage strategic and technical partners
- Familiarity with data science, computer vision, digital health space. Knowledge of Immunology. Knowledge of relevant healthcare datasets, such as EHR, or insurance claims.
Preferred
- Advanced degree (e.g., MD, PhD, MBA or equivalent)
- Experience delivering data science projects using predictive technologies, data mining and/or text mining
- Experience analyzing or handling healthcare data sets, including EHR, claims, registry data, and images
- Experience with data science tools and statistical programming languages, including SQL, Python, R, and others
- Experience with defining use cases for deep learning, foundational models, machine learning and artificial intelligence in diagnostic medical imaging and digital health sensing data
- Ability to travel 25%, domestic and global
The primary and preferred location for this position is San Diego, CA. Consideration may be given for candidates who are or can be located near Spring House, PA; Titusville, NJ; or Cambridge, MA. This role currently follows a hybrid schedule of three days in the office and two days remotely per week (no fully 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.
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 (ra-employeehealthsup@its.jnj.com) or internal candidates 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.
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Required Skills:
Preferred Skills:
Advanced Analytics, Consulting, Critical Thinking, Data Analysis, Data Privacy Standards, Data Quality, Data Reporting, Data Savvy, Data Science, Data Visualization, Developing Others, Digital Fluency, Roadmapping, Statistical Computing, Strategic Thinking, Tactical Planning, Technical Credibility
Salary Context
This $164K-$282K range is above the 75th percentile for AI/ML Engineer roles in our dataset (median: $170K across 217 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 37,339 AI roles we're tracking, AI/ML Engineer positions make up 91% of the market. At Johnson & Johnson, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $154,000 based on 8,743 positions with disclosed compensation. Director-level AI roles across all categories have a median of $230,600. This role's midpoint ($223K) sits 45% above the category median. Disclosed range: $164K to $282K.
Across all AI roles, the market median is $190,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $300,688. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Safety ($274,200). By seniority level: Entry: $85,000; Mid: $147,000; Senior: $225,000; Director: $230,600; VP: $248,357.
Johnson & Johnson AI Hiring
Johnson & Johnson has 2 open AI roles right now. They're hiring across AI/ML Engineer. Positions span Spring House, PA, US, San Diego, CA, US. Compensation range: $282K - $342K.
Location Context
Across all AI roles, 7% (2,732 positions) offer remote work, while 34,484 require on-site attendance. Top AI hiring metros: New York (1,633 roles, $204,100 median); Los Angeles (1,356 roles, $179,440 median); San Francisco (1,230 roles, $240,000 median).
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 37,339 open positions tracked in our dataset. By seniority: 3,672 entry-level, 23,272 mid-level, 7,048 senior, and 3,347 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (2,732 positions). The remaining 34,484 roles require on-site or hybrid attendance.
The market median for AI roles is $190,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $300,688. Highest-paying categories: AI Engineering Manager ($293,500 median, 21 roles); AI Safety ($274,200 median, 24 roles); Research Engineer ($260,000 median, 264 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 37,339 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (33,926), AI Software Engineer (823), AI Product Manager (805). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (3,672) are outnumbered by mid-level (23,272) and senior (7,048) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 3,347 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (2,732 positions), with 34,484 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $190,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $300,688. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $145,600. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Rag (23,721 postings), Aws (12,486 postings), Rust (10,785 postings), Python (5,564 postings), Azure (3,616 postings), Gcp (3,032 postings), Prompt Engineering (2,112 postings), Kubernetes (1,713 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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