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 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:

• Use API calls to extend functionality and integration with packaged NLP, vision, and GenAI services
• Develop dial management systems to manage the flow of conversation including handing context, maintaining state, and deciding appropriate responses based on user inputs
• Integrate the conversational AI with backend systems and databases to retrieve information or perform appropriate actions based on user requests
• Train and fine-tune models based on real user interactions to improve the AI understanding and responsiveness
• Test and resolve bugs to ensure the AI behaves as expected across various scenarios and user inputs.
• Monitor and optimize performance of the AI systems that you work with

• 1 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