Applied AI Scientist, Immunology Discovery

6084-Janssen Research & Development, LLC Legal Entity; Cambridge (MA); On-site; USD 115,000 - 227,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Retirement plan

Paid time off

Job summary

Johnson & Johnson in Cambridge, MA seeks a Principal Scientist, Applied AI in Immunology Discovery to design, build, and pilot AI-enabled solutions. You will partner with scientists, computational colleagues, and enterprise teams to translate biological questions into reusable capabilities that can scale.

The role requires a PhD and 4+ years of relevant experience, strong Python/R skills, and hands-on experience with generative AI, LLMs, and AI-driven workflows within a regulated biopharma

Qualifications

• PhD in AI/computational science or related field.
• 4+ years industry or applied research experience.
• Experience building AI solutions in R or Python.
• Experience with generative AI and LLMs.
• Ability to translate scientific needs into requirements.
• Strong communication across disciplines.

Responsibilities

• Build AI prototypes across scientific use cases.
• Develop AI solutions and copilots.
• Translate scientific needs into requirements and hypotheses.
• Collaborate with scientists and end users to gather feedback.
• Evaluate accuracy, reliability, usability, and impact.
• Work with enterprise AI and data science teams to scale prototypes.

Skills

AI/ML

Python

R

Generative AI

LLMs

Product thinking

Collaboration

Time management

Education

PhD in AI/Comp Sci

Tools

Cloud computing

Containers

Git

APIs

Job description

Johnson & Johnson in Cambridge, MA seeks a Principal Scientist, Applied AI in Immunology Discovery to design, build, and pilot AI-enabled solutions. You will partner with scientists, computational colleagues, and enterprise teams to translate biological questions into reusable capabilities that can scale.

The role requires a PhD and 4+ years of relevant experience, strong Python/R skills, and hands-on experience with generative AI, LLMs, and AI-driven workflows within a regulated biopharma