AI Machine Learning Engineer

$104,000 - $750,000/Yr

Janssen Global Services - Hopewell Township, NJ

Full-time - Senior

Hopewell Township, NJ

About the position

Johnson & Johnson Innovative Medicine is seeking an innovative and motivated AI Machine Learning Engineer to lead the development of AI/ML solutions across Commercial North America. This position is primarily located in Titusville, New Jersey. At J&J Innovative Medicine, our mission is to help people live full and healthy lives by focusing on treating, curing, and preventing some of the most devastating diseases of our time. We are committed to pursuing the most promising science, regardless of where it may be found. Our company provides medicines for a variety of health concerns across several therapeutic areas, including Cardiovascular, Metabolic, Mental Health, and Pain Management. We pride ourselves on fostering a diverse company culture that celebrates the uniqueness of our employees and is committed to inclusion. As an equal opportunity employer, we encourage all qualified applicants to apply. In this role, the AI Machine Learning Engineer will play a key role in the AI-enabled transformation of medical engagement through both personal and non-personal channels. The engineer will be responsible for shaping and developing new AI, ML, and other Data Science initiatives within J&J Innovative Medicine's Commercial North America sector. This includes acting as the technical lead for machine learning, AI, and data engineering solutions and products, collaborating with peers across technology and business functions to define and develop new solutions and operations. The engineer will also be tasked with creating end-to-end AI/ML pipelines that integrate seamlessly into products throughout the product lifecycle, from proof-of-concept (POC) to production, scaling, ongoing enhancements, and maintenance (ML Operations). Additionally, the role involves leading technical projects and taking end-to-end responsibility for AI/ML solutions. The engineer will 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.

Responsibilities

• Lead the shaping and development of AI/ML solutions across Commercial North America.
• Act as the technical lead for machine learning, AI, and data engineering solutions and products within Commercial NA.
• Collaborate with peers across technology and business functions to define and develop new Machine Learning, AI, and Data Engineering Solutions and Operations.
• Rapidly prototype and integrate machine learning and AI models into technology products.
• Create end-to-end AI/ML pipelines that integrate seamlessly into products through the product lifecycle.
• Lead technical projects, taking end-to-end responsibility for AI/ML solutions.
• Coordinate technical seminars, training sessions, and workshops focused on AI/ML.

Requirements

• PhD in a quantitative discipline such as software engineering, computer science, statistics, biostatistics, or supply chain; or an equivalent educational background of MS with 3+ years or BS with 5+ years of experience in building AI/ML solutions in the healthcare industry.
• Proficient in exploratory data analysis, data transformation, feature creation & engineering, and data visualization using SQL, Python, PySpark, and associated machine learning packages such as TensorFlow, PyTorch, and Keras.
• Strong expertise in building and deploying machine learning models such as generalized linear regression, logistic regression, XGBoost, random forest, neural networks, NLP, GenAI, or large language model (LLM).
• Experience with deploying data/model pipelines in machine learning platforms such as AWS (SageMaker, Argo, Kedro), Docker, Databricks, Dataiku.
• Experience in setting up, configuring, and managing CI/CD pipelines with frameworks such as Docker, Kubernetes, Helm, Jenkins, and Gitlab.
• Strong presentation skills for diverse technical and/or business audiences.

Nice-to-haves

• Proven success in applying Data Science and ML engineering methods to solve Scientific and Medical Affairs problems in the Pharma industry.
• Experience working in a fast-paced environment with competing priorities, multiple stakeholders, matrixed teams, and evolving needs.
• Experience working in cross-functional teams to deliver outstanding results.