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Egen Solutions

Senior Machine Learning Engineer

Egen Solutions, Naperville, Illinois, United States, 60564


Egen is a fast-growing and entrepreneurial company with a data-first mindset. We bring together the best engineering talent working with the most advanced technology platforms, including Google Cloud and Salesforce, to help clients drive action and impact through data and insights. We are committed to being a place where the best people choose to work so they can apply their engineering and technology expertise to envision what is next for how data and platforms can change the world for the better. We are dedicated to learning, thrive on solving tough problems, and continually innovate to achieve fast, effective results.

We are looking for a Senior Machine Learning Engineer to assist in developing implementation patterns across natural language and generative AI practices. You will be responsible for delivering systems design and architecture, documenting requirements, and making design decisions.

Responsibilities:

Lead delivery teams and clearly delineate parallel work-streams

Lead discovery sessions with clients and carefully navigate requirement discussions to avoid designs requiring additional scope

Support pre-sales discussions and assist pre-sales engineers to identify scope issues and clearly define assumptions for LOEs

Drive reusable code and solution architecture practice

Apply cloud architecture and application design knowledge

Assist the sales team with potential clients

Document requirements and design decisions

Ensure coding practices result in clean, reusable code to consistently mature the delivery practice

What we're looking for:

5+ years of experience as a ML Engineer

Bachelor’s Degree is preferred but will consider relevant experience as an equivalent

Strong foundation in NLP, vision, and generative AI

Vertex AI, Vertex Search and Conversations

Dialogflow CX

Vision AI and OCR

Cloud Text-to-Speech, Cloud Speech-to-Text

Cloud Translation, Glossaries

Python

Vector stores

Langchain

Data Loss Prevention

CICD best practices, especially with complexity of CCAI and/or PSO engagements

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