Senior Gen AI Engineer

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Requirements:

• 5+ years of relevant work experience in analytics, technology, software engineering, or healthcare (academic experience included), or related equivalent experience.
• 3+ years of hands-on experience specifically with machine learning, deep learning, and preferably Generative AI models (e.g., LLMs, diffusion models) is required.
• Proven experience handling large, complex datasets to build and optimize sophisticated data science pipelines.
• Deep experience with Machine Learning, Deep Learning frameworks (e.g., Pytorch, TensorFlow), Natural Language Processing (NLP), and associated libraries (e.g., Hugging Face Transformers).
• Experience deploying and managing ML models in cloud environments (GCP Vertex AI preferred, AWS SageMaker or Azure ML acceptable).
• Expert proficiency in Python and relevant data science/ML libraries.

Responsibilities:

• Lead the ideation, development, and productionalization of sophisticated Generative AI solutions tailored for healthcare payer use cases.
• Architect, design, and implement complex, state-of-the-art Generative AI models and algorithms, leveraging Python and cloud platforms like GCP Vertex AI.
• Partner strategically with product teams and business stakeholders to define and prioritize opportunities for applying advanced Generative AI techniques to solve critical business challenges and drive process automation.
• Conduct in-depth research and maintain expertise in the latest advancements in Generative AI, championing the adoption of cutting-edge techniques and methodologies within the team.
• Architect and develop robust, scalable, and efficient systems and code bases for deploying Generative AI models into production environments, ensuring high availability and performance.
• Serve as a key technical advisor to our internal Lines-of-Businesses, understanding complex needs, gathering requirements, and translating them into impactful, actionable AI solutions.
• Define and oversee the evaluation and validation frameworks for Generative AI models, ensuring their accuracy, reliability, fairness, and performance exceed business requirements.
• Mentor and guide junior engineers on best practices in AI development, model implementation, and system design.