ML Engineer

Summary

As a Machine Learning Engineer at Gateway, you will work on leveraging large language and action models at scale to power our products. As a key member of the AI team, you will be working with other talented engineers to drive the development of novel agentic AI techniques, and integrate these new techniques into multiple product lines.


Responsibilities

Work closely with the backend team to design, develop, test, and maintain large language models, large action models and agents leveraging them at scale 

Develop novel agentic architectures around LLMs and LAMs to serve multiple products 

Collaborate on the architecture and engineering of our AI infrastructure to ensure it is robust, scalable, maintainable and performant for multiple AI products 

Drive and own development projects from concept through production. This includes research, prototyping, design, implementation, testing, documentation, training, and maintenance.

Work with other cross-functional teams such as product management to help design the AI systems and models that power our products


Requirements

At least 1 year experience with large language models (LLMs) / transformer models.

At least 1 year experience with agentic development frameworks using LLMs (LangChain, LlamaIndex, etc)

At least 1 year experience with neurosymbolic AI and RAG systems.

Excellent written and verbal communication skills.

Strong problem solving skills to resolve complex problems in creative ways

Ability to work independently as well as within a team


Preferred

Ph.D or MS  in ML/AI or a related field

Hands-on experience with all stages of LLM training and inference

Experience in reinforcement learning (RL) techniques
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