Senior Data Scientist at Flexjet in Cleveland, OH

POSITION SUMMARY Flexjet is seeking a Senior-Level Enterprise AI Data Scientist to design, develop, and deploy enterprise-scale AI and Generative AI solutions that improve productivity, automate workflows, and enhance decision-making across the organization. This role focuses on building LLM-powered enterprise applications, such as internal knowledge assistants, document processing systems, and workflow automation tools. The ideal candidate has hands-on experience with machine learning, large language models (LLMs), Retrieval-Augmented Generation (RAG), and enterprise data systems. Collaborate with data engineers, software engineers, product teams, and business stakeholders to build secure, scalable, and production-ready AI solutions that align with enterprise governance and compliance standards. DUTIES & RESPONSIBILITIES · Design and implement enterprise-scale machine learning models, including predictive and classification systems · Develop intelligent automation solutions to streamline business workflows · Build and deploy LLM-powered applications, such as enterprise knowledge assistants and chatbots · Design and implement Retrieval-Augmented Generation (RAG) pipelines · Develop solutions for semantic search, document intelligence, and enterprise search capabilities · Optimize prompt engineering workflows and fine-tune models using domain-specific data · Evaluate and benchmark machine learning and LLM model performance · Work with large-scale structured and unstructured data sources across enterprise systems · Design and build scalable data pipelines to support AI and machine learning workflows · Integrate AI solutions with internal systems, APIs, and enterprise platforms · Partner with data engineering teams to design and optimize data architectures · Deploy AI/ML models into production environments · Implement model monitoring, performance tracking, and alerting · Maintain model versioning, reproducibility, and lifecycle management · Support and contribute to CI/CD pipelines for AI and ML deployments · Ensure scalability, reliability, and performance of systems in production environments · Implement responsible AI practices, including fairness, transparency, and risk mitigation · Ensure compliance with enterprise data governance, privacy, and security standards · Support model explainability and documentation requirements · Maintain thorough documentation of models, systems, and workflows · Translate business needs into actionable technical solutions · Work closely with product, engineering, and analytics teams to deliver AI-driven solutions · Communicate technical concepts and solutions clearly to non-technical stakeholders · Contribute to system architecture decisions and design discussions · Document workflows, design decisions, and results EDUCATION & EXPERIENCE · Bachelor's or master's degree in computer science, Information Technology, Data Science, or a related field, or an equivalent combination of education, training, and relevant professional experience. · 5+ years of experience in Data Science, Machine Learning, and AI software engineering, machine learning engineering, platform engineering, MLOps, or DevOps. · Experience building and deploying production ML systems · Hands-on expertise in data preprocessing, feature engineering, and model evaluation · Experience working with APIs, large datasets, and enterprise systems REQUIRED TECHNICAL SKILLS & QUALIFICATIONS · Programming: Strong proficiency in Python and SQL · Experience developing and deploying models (regression, classification, clustering, ensembles, neural networks) · Strong understanding of data preprocessing, feature engineering, and model evaluation · Prompt engineering and optimization · Retrieval-Augmented Generation (RAG) · Embeddings and vector search · Model evaluation and fine-tuning · Experience working with large, complex datasets · Data pipelines, ETL processes, and enterprise data warehouses · API integrations and distributed/enterprise-scale systems · Deployment & Infrastructure: · Building and maintaining production-ready ML systems · Familiarity with Docker, Kubernetes, and REST APIs · CI/CD pipelines and version control (Git) · Experience with AWS, Azure, or Google Cloud PREFERRED QUALIFICATIONS · Experience developing LLM-powered applications in enterprise environments · Hands-on experience with RAG pipelines, embeddings, and vector databases · Strong understanding of prompt engineering and LLM evaluation techniques · Familiarity with frameworks such as LangChain, LlamaIndex, and Hugging Face · Knowledge of MLOps practices, including CI/CD, model monitoring, and lifecycle management · Experience with Docker, Kubernetes, and containerized deployments · Understanding of data governance, responsible AI, and model explainability