Senior Data Scientist, ML Operations & Gen AI

- Design and develop production-grade Machine Learning Operations and Generative AI solutions. - Lead the hands-on implementation of scalable GenAI solutions from initial problem framing through prototyping, evaluation, and production monitoring. - Create internal copilots/assistants (such as knowledge search, code/content generation) and customer-facing products (including conversational analytics, summarization, recommendations, and workflow automation). - Design RAG pipelines, embedding strategies, vector searches, and model orchestration; assess the effectiveness of fine-tuning versus prompt engineering. - Implement guardrails, safety filters, prompt/version management, and optimize latency/throughput and cost controls. - Identify areas for improvement or additional functionalities within the ML platform and use expertise to design and develop solutions that fill these gaps. Analyze system performance for scalability and reliability to uncover enhancement opportunities. - Collaborate with infrastructure teams to ensure the seamless integration and deployment of ML solutions, optimizing scalability, performance, and reliability of AI Team outputs by adopting industry best practices. - Streamline data workflows, including ingestion, preprocessing, feature engineering, and model training, to improve efficiency and reduce latency, working closely with data engineering teams. - Evaluate and enhance model prototypes for real-world adaptability, collaborating with infrastructure and development teams to incorporate ML models into production systems and communicate technical requirements effectively. - Work alongside our Data Science team to implement and operationalize AI/ML models, ensuring successful collaboration with other machine learning engineers, data scientists, and software engineers. Responsibilities include applying engineering best practices to machine learning.