AI/ML Engineer

University of Denver; Atlanta (GA); Remote; USD 90,000 - 130,000; Full time

Job summary

University of Denver is hiring an AI Engineer to design, build, and deploy Generative AI solutions across the U.S. You will work with experienced engineers to develop ML models, data pipelines, and AI-powered applications using Python and modern ML frameworks.

Responsibilities include data preprocessing, model training, evaluation of outputs, and documentation for reproducibility. The role emphasizes responsible AI and collaboration with product and engineering teams in a fast-paced environment.

Qualifications

• Bachelor’s or Master’s degree in AI/CS/DS or related field.
• Strong foundation in Python and ML libraries; solid understanding of ML lifecycle.

Responsibilities

• Assist in building, training, and fine-tuning machine learning and Generative AI models.
• Perform data preprocessing, feature engineering, and exploratory data analysis (EDA).
• Develop AI-powered applications using Python and ML frameworks.
• Evaluate LLM outputs for accuracy, quality, factuality, and bias.
• Document model behavior, dataset usage, and training workflows for reproducibility.
• Collaborate with cross-functional teams for testing and integration.
• Stay up to date with AI advancements, tools, and research trends.

Skills

Python

NumPy

Pandas

Scikit-learn

TensorFlow

PyTorch

LLM

Prompt engineering

LangChain

Hugging Face

OpenAI APIs

Azure OpenAI Service

Education

Bachelor’s or Master’s degree in Artificial Intelligence, Computer Science, IT, Data Science, or related fields

Tools

LangChain

Hugging Face

OpenAI APIs

Azure OpenAI Service

Job description

Location: We are hiring for roles across multiple locations within the United States.

About the Role

We are looking for a passionate and driven AI Engineer to join our growing AI team in the United States. In this role, you will collaborate with experienced engineers and architects to design, build, and deploy innovative AI/ML and Generative AI solutions.

This is an exciting opportunity to gain hands‑on experience across the entire AI lifecycle—from data preparation and model development to evaluation and real‑world deployment—while working on cutting‑edge technologies such as LLMs, RAG pipelines, and agentic AI systems.

Key Responsibilities

• Assist in building, training, and fine‑tuning machine learning and Generative AI models
• Perform data preprocessing, feature engineering, and exploratory data analysis (EDA)
• Develop AI-powered applications using Python and common ML frameworks
• Evaluate LLM outputs for accuracy, quality, factuality, and bias
• Document model behavior, dataset usage, and training workflows for reproducibility
• Collaborate with cross-functional teams (product, engineering, data) for testing and integration
• Stay up to date with the latest AI advancements, tools, and research trends

Education

• Bachelor’s or Master’s degree in Artificial Intelligence, Computer Science, IT, Data Science, or related fields

Technical Skills

Programming & Machine Learning

• Strong proficiency in Python
• Hands‑on experience with NumPy, Pandas, Scikit‑learn
• Basic understanding of TensorFlow or PyTorch

GenAI & LLM Foundations

• Familiarity with LLMs, embeddings, and prompt engineering
• Understanding of GPT, BERT, and generative models such as GANs, VAEs, Diffusion models

Tools & Frameworks

• Exposure to LangChain, Hugging Face, OpenAI APIs, Azure OpenAI Service

Cloud & Advanced AI Concepts

• Awareness of Azure AI, AWS Bedrock, Google Vertex AI
• Basic understanding of RAG pipelines, vector databases (Pinecone, FAISS)
• Knowledge of Agentic AI and Model Context Protocol (MCP) fundamentals
• Familiarity with CI/CD practices for AI workflows

Responsible AI & Quality

• Awareness of AI fairness, bias, privacy, and responsible AI principles
• Understanding of model evaluation metrics and LLM‑specific challenges such as hallucination detection and factual accuracy

Soft Skills

• Strong curiosity and eagerness to learn
• Effective communication and collaboration skills
• Analytical thinking with a structured problem-solving approach
• Willingness to experiment, iterate, and innovate

Nice‑to‑Have (Preferred)

• Certifications such as:
  • Azure AI Engineer Associate
  • AWS Machine Learning Specialty
  • Google Professional ML Engineer
  • Databricks certifications
• Internship or academic project experience in AI/ML or Generative AI

Why Join Us

• Work on cutting‑edge AI and GenAI initiatives
• Gain mentorship from experienced AI architects and engineers
• Exposure to real‑world, large-scale AI deployments
• Dynamic, innovative, and collaborative work environment across the U.S.