Associate AI Engineer

United States·ChicagoFull Timemid

Machine Learning EngineerAI EngineerDataData & AI

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Quick Summary

Overview

AHEAD builds platforms for digital business. By weaving together advances in cloud infrastructure, automation and analytics, and software delivery,

Technical Tools

anthropicawsazuredockerfastapiflaskgcpkubernetesopenaipythonci-cdetl

AHEAD builds platforms for digital business. By weaving together advances in cloud infrastructure, automation and analytics, and software delivery, we help enterprises deliver on the promise of digital transformation.

At AHEAD, we prioritize creating a culture of belonging, where all perspectives and voices are represented, valued, respected, and heard. We create spaces to empower everyone to speak up, make change, and drive the culture at AHEAD.

We are an equal opportunity employer, and do not discriminate based on an individual's race, national origin, color, gender, gender identity, gender expression, sexual orientation, religion, age, disability, marital status, or any other protected characteristic under applicable law, whether actual or perceived.

We embrace all candidates that will contribute to the diversification and enrichment of ideas and perspectives at AHEAD.

Innovative Thinkers

Enthusiastic Collaborators

Creative Problem Solvers

Curious Self – Starters

Ability to communicate effectively across teams, and build positive relationships

Demonstrate ability to work on teams, collaborate on projects, and contribute to the overall successful delivery of projects

Demonstrate drive and proactiveness to get things done, be solutions–oriented, and enjoy solving complex problems

Demonstrate resourcefulness, curiosity, creativity, courage, critical thinking, and a desire to use technology to search for new and innovative solutions to problems

Exercise sound reasoning, ingenuity, and inclusive perspectives to analyze issues, solve problems and make recommendations

Ability to execute, manage competing priorities, and deliver to deadlines

Working knowledge of AI/ML fundamentals, including model types (transformers, embeddings, diffusion), data pipelines, and inference workflows

Proficiency in Python, with exposure to frameworks such as FastAPI, Flask

Familiarity with GenAI tooling (OpenAI, Anthropic, Gemini, etc.) and vector stores (Pinecone, FAISS, Weaviate)

Exposure to cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes)

Understanding of MLOps concepts—version control (Git, DVC), CI/CD, observability, and deployment best practices

Experience in at least one of the following:

Academic or personal AI/ML projects

Internship or co-op in software or data engineering

Technical bootcamp or certificate program in AI, ML, or cloud computing

Certifications such as AWS Cloud Practitioner, Microsoft MS-900, or GCP Cloud Engineer are a plus