AI Engineer

Medpace, Inc.•Cincinnati, OH

9d•Hybrid

About The Position

We are currently seeking a professional with experience with artificial intelligence (AI) tools such as NLP, LLM, IA etc. This professional will be programming and fine-tuning various AI tools and helping IT teams to implement them into new applications. This professional will work collaboratively across the organization with multiple teams to improve the efficiency of company processes and provide insights and assistance to users.

Requirements

Bachelor’s degree or higher in Artificial Intelligence, Computer or Data Science, or related field. Master’s degree preferred
Proven experience implementing and fine-tuning Large Language Models or interactive AI applications (>1 year post-graduate experience)
Technical proficiency in programming languages and frameworks commonly used in NLP and AI (e.g., Python, TensorFlow, PyTorch)
Excellent communication skills to collaborate effectively with cross-functional teams
A passion for staying up-to-date with the latest advancements in NLP and AI technologies
Analytical thinker with great attention to detail

Nice To Haves

Preferably several years of experience working with different AI capabilities and showcasing your passion both at work and outside work in the utilization of AI

Responsibilities

Design, implement, and deploy machine learning models and systems to solve complex problems and drive business outcomes
Research, develop, and implement machine learning algorithms and models for tasks such as classification, regression, clustering, anomaly detection, and recommendation systems
Research, develop, and implement AI tools such as NLP, LLM, and IA
Collect, preprocess, and curate large datasets required for training generative models
Experiment with different machine learning techniques and algorithms, including supervised, unsupervised, semi-supervised, reinforcement, and deep learning
Design and optimize machine learning pipelines and workflows, incorporating techniques for data cleaning, feature engineering, model selection, and hyperparameter tuning
Develop scalable and efficient machine learning infrastructure and systems for training, testing, and deploying models in production environments