Artificial Intelligence (AI) Architect

Info Origin - Raritan, NJ

Full-time

Raritan, NJ

Professional, Scientific, and Technical Services

About the position

The Artificial Intelligence (AI) Architect role focuses on the development, deployment, and maintenance of machine learning models and pipelines. This position is responsible for ensuring scalable solutions across multiple brands, automating model refreshes, and providing end-to-end support for MLOps platforms. The architect will also be involved in quality control, performance reporting, and troubleshooting to optimize pipeline efficiency.

Responsibilities

• Development and Testing experience with Data Science Models.
• End-to-end model and pipeline support while producing reusable solutions for scalable use across multiple brands.
• Migration of machine learning models, pipelines, python scripts, etc. into MLOps platforms (Dataiku, databricks, MLFlow).
• Deployment of ML solutions for delivery into the field.
• Automating model refreshes and pipeline runs with output validation and monitoring.
• Developing quality control checks and automated alerts.
• Pipeline maintenance, troubleshooting, and documentation.
• Pipeline optimization (run-time and stability).
• Delivering reports on model performance, drift, pipeline run times, issue trackers, etc.

Requirements

• M.S. with 2+ years, or B.S. with 3+ years, of relevant MLOps experience or data engineering experience, in Computer Sciences, Mathematics, Statistics, Machine Learning & Artificial Intelligence, Physics, Engineering, Bioinformatics, Computational Biology or a related discipline.
• Experience deploying and operationalizing machine learning models.
• Experience creating and enacting strategy for automated model refreshes and pipeline runs, including automated QC checks, tracking model drift, and validating pipeline output.
• Experience diagnosing pipeline performance issues or crashes.
• Experience with MLOps platforms such as Dataiku, MLFlow, databricks, etc.
• Proficiency in Python and SQL.
• Familiarity with PySpark.
• Ability to manage and monitor multiple deployed solutions simultaneously.
• Proficient with source control platforms such as GitHub or BitBucket.
• Experience working with AWS or cloud platforms.
• Strong communication skills and ability to communicate complex methods and results to diverse audiences both technical and non-technical.
• Understanding of fundamentals underlying common machine learning models.

Nice-to-haves

• Experience in the commercial pharmaceuticals business.
• Experience automating solutions for rapid use across projects.
• Experience in pipeline optimization with track record of reducing runtimes.