AI Engineer (Python, Machine Learning, Generative AI/LLMs)

Founded in 2011, Modus is a global, fully remote team of world-class technologists who thrive in a collaborative, innovative environment.

We’re a digital product engineering partner for forward-thinking businesses.

Our global teams work side-by-side with clients to design, build, and scale custom solutions that achieve real results and lasting change, partnering with industry leaders including AWS, GitHub, and Atlassian.

We were fully remote before it was cool!

Recognized as one of the Inc. 5000 Fastest Growing Private Companies for nine years and a top remote work company by FlexJobs, we have helped some of the world’s largest brands deliver powerful digital experiences.

As an award-winning Atlassian partner with a world-class team, we help organizations innovate and solve complex challenges for Fortune 500 companies and beyond, we want to hear from you.

Opportunity!

We are looking for an AI Engineer to join our engineering team and design, build, and deploy intelligent solutions using modern Machine Learning, Deep Learning, and Generative AI technologies.

You’ll work across the AI/ML lifecycle, from experimentation and model development to integration and production deployment, collaborating with engineering, product, and data teams to turn complex business challenges into scalable AI-powered solutions.

• Strong proficiency in Python and experience developing production-ready AI/ML applications and services.
• Solid experience with Machine Learning , including model development, evaluation, optimization, and implementation.
• Hands-on experience building applications using Generative AI and Large Language Models (LLMs) .
• Experience with Deep Learning concepts, neural networks, and modern model architectures.
• Practical experience with PyTorch and/or TensorFlow .
• Experience with Natural Language Processing (NLP) , including areas such as text processing, embeddings, semantic search, classification, or generation.
• Hands-on experience designing and implementing Retrieval-Augmented Generation (RAG) pipelines and working with vector-based retrieval.
• Experience integrating AI/ML APIs, foundation models, and third-party AI services into applications.