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# Senior AI/ML Engineer

- **Company:** Johnson & Johnson
- **Location:** Hopewell Township, NJ, United States (Remote available)
- **Experience:** Expert
- **Salary:** $155,000.0 - $175,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Artificial Neural Networks, System Configuration, Continuous Integration, Database Schema, Monitoring of Systems, Python (Programming Language), Linear Regression, Logistic Regression, Machine Learning, Language Modeling, Natural Language Processing, Systems Development Life Cycle, Tensorflow, Software Deployment, Software Engineering, Pytorch, Delivery Pipeline, Large Language Models, Random Forest, Keras, Gitlab, Build Management, Kubernetes, Information Technology, Production Code, Xgboost, Data Management, Machine Learning Operations, Virtual Agents, Data Pipelines, Docker, Jenkins
- **Published:** September 15, 2026
- **Apply:** https://www.careerjet.com/job/us5240f7375a4b732b4a7b3a6a6810c391/eaa

## About the Role

Requirements: Employer will accept a Master's degree in Business Analytics, Software Engineering, Computer Science, Statistics, or related field and 3 years of experience in the job offered or in a Senior AI/ML Engineer-related occupation.
Position requires experience with:

 1. Building end-to-end data products, from POC stage through the full product life cycle including operationalization and scaling;
 2. Python or R along with associated machine learning packages TensorFlow, PyTorch, and Keras;
 3. Setting up, configuring, and managing CI/CD pipelines to ensure smooth and efficient software development workflows, with frameworks including Docker, Kubernetes, Helm, Jenkins, and Gitlab;
 4. Building and deploying machine learning models including generalized linear regression, logistic regression, XGBoost, random forest, neural networks, NLP, and GenAI or large language model (LLM); and
 5. AI-enabled transformation and thought leadership, including project management.

## Description

Job Duties: Shape and develop AI/ML and other Data Science initiatives across J&J Innovative Medicine. Serve as subject matter expert in ML Engineering with a focus on end-to-end product engineering. Help shape the software development lifecycle of data science products including but not limited to coding best practices, technical back-end support, CI/CD frameworks, and model monitoring. Create end-to-end AI/ML pipelines that integrate seamlessly into products through the product lifecycle, starting from proof-of-concept (POC) phase, moving into production, scaling, ongoing enhancements, and maintenance (ML Operations). Partner with senior leaders and peers across technology and business functions to shape new AI and ML solutions and operations. Partner closely with cross-functional technical teams to ensure strong delivery. Play a key role in the AI-enabled transformation of Commercial engagement through personal and non-personal channels, and other high visibility projects that drive
impact for patients and for J&J Innovative Medicine. Coordinate technical seminars, training sessions, and workshops focused on AI/ML to enhance the skills of data scientists, data engineers, and other technology professionals across the organization. Design and build predictive ML models that identify and prioritize patients and healthcare providers most relevant to specific medicines, brands, and therapeutic areas, in order to predict clinically and commercially significant outcomes such as patient-identification and therapy-tolerance model products. Design and build Agentic AI systems built on large and small language models (LLMs and SLMs) that autonomously carry out multi-step commercial-engagement and analytics workflows, together with engineering platforms required to operate, evaluate, and measure those systems reliably and in compliance with healthcare-data regulations. Partner with engineering and infrastructure leaders, external data-science and platform-engineering
vendor teams, and commercial business stakeholders to define what each system must do and how its quality and business value are measured. Shape and develop AI/ML and data science initiatives including individual modeling programs (such as the hematology/oncology patient-identification and therapy-tolerance modeling programs) and enterprise AI-platform initiatives (such as the agent-evaluation framework, the conversational-analytics platform, and the Agent observability platform), spanning the full range from early problem framing and architecture through hands-on implementation and production deployment. Design and build the core models, pipelines, frameworks, and agent tools; define their technical architecture and data schemas; write and integrate production code; and establish the engineering standards for the team. Design, build, and validate the core components of end-to-end AI/ML product pipelines, including for model development, agent evaluation, conversational analytics, and
agentic data pipelines. Define SDLC coding and architecture standards; establish code-review and pull-request workflows and integration standards; define CI/CD and containerized deployment practices. Design evaluation and quality gates that determine whether a model or AI agent is reliable enough to promote to production. Define production monitoring and ongoing evaluation to detect and correct production issues after deployment.
May telecommute per company policy (hybrid).


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