AI Engineer

Overview

The Emmes Company, LLC (“Emmes”) is a global, full-service Clinical Research Organization dedicated to excellence in supporting the advancement of public health and biopharmaceutical innovation. We believe in the power of truth, so much so that we named our company Emmes, which means truth. Through decades of experience we have learned that collaborative relationships thrive and human health benefits when truth is our compass.

Our “Character Achieves Results” culture is driven by five key values that guide our actions in the way we conduct research and distinguish us as an organization: Integrity, Agility, Passion for Excellence, Collaborative Partnerships and Intellectual Curiosity. We are a trusted partner to clients who share our passion for improving public health in a world of ever-changing scientific research.

If you share our motivations and passion in research, come join us! You will be joining a collaborative culture that empowers every Emmes employee — from entry level through top executive — to contribute to our clients’ success by sharing ideas openly and honestly.

Primary Purpose

Developing and deploying innovative AI solutions using the AWS technology stack. You will be responsible for assisting with automation of the entire AI lifecycle, from data staging, model training and development to deployment, monitoring, and application integration

Responsibilities

• Design, develop, and deploy machine learning models using AWS services such as Bedrock, Titan, Comprehend, SageMaker as well as Rekognition and Transcribe.
• Effectively integrate, automate, and optimize data pipelines for model training and inference using AWS Glue, S3, and Lambda.
• Implement effective AWS infrastructure for training, testing, and deployi ng machine learning models, including deep learning models such as large language models (LLMs) and integration of foundation models.
• Monitor and maintain deployed models in production, ensuring high performance and accuracy.
• Collaborate with data engineers, data scientists and software engineers to integrate AI models into existing applications and systems.
• Stay up-to-date on the latest advancements in AI and AWS technologies.
• Benchmark and optimize computational performance of AI modeling processes.
• Document and communicate technical findings and solutions effectively.