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Location
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Location Preference:
1st Preference: Hartford, CT – Whole team is onsite at Hartford, CT so this location will be first preference. Any nearby location will also work if candidate is willing to relocate from Day 1.
2nd Preference: Candidates will relocate to Hartford, CT.
3rd Preference: Candidates from Richardson, TX, Minneapolis, MN. They will be working from Health Care Company office in this location.
4th Preference: Candidates from NY, NJ and Boston region who are willing to travel as needed to Hartford office and rest of the days they can work remote. This is the least preferred option.
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Job Description
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Detailed Job Description:
Collaborate with cross-functional teams to understand business requirements and translate them into scalable and efficient AI solutions.
Should have 2-3 years of Architecture experience – Mandatory
Candidates should be hands on AI/ML development - Mandatory
Experience in using Google CCAI (Contact Center AI) /CES (Customer Experience Suite) platform and it's components.
Advanced experience in production grade Machine Learning Model design and implementation including LLMs, Model Evaluation and MLOps.
In depth exposure and experience in designing and implement machine learning models using Google Vertex AI & Python in the context of Conversational AI.
Design, build, and deploy machine learning models on the Google Cloud Platform.
Experience in agentic architecture-based implementations and advanced Retrieval Augmented Generation.
Conduct thorough testing and validation to ensure the accuracy and reliability of the models. Experience in Eval frameworks and eval metrics.
Optimize and fine-tune machine learning models for performance, efficiency, and accuracy. Experience in Parameter Efficient Fine Tuning will be an added advantage.
Stay updated on the latest advancements in machine learning and AI technologies.
Ability to directly deal with tech experts from product companies such as google and drive solutions to meet customer expectations, goals
Maturity working in a customer environment with understanding the boundaries.
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