AI Engineer

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October 16

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Cayuse Holdings

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Government • B2B • Cybersecurity

Cayuse Holdings is a company that represents a portfolio of businesses focused on delivering IT services across various sectors, including Government, Commercial, and Native Solutions. The company prioritizes long-term relationships with clients and provides a wide range of services, such as program and project management, cybersecurity operations, and systems implementation. With a commitment to sustainability and stewardship, Cayuse Holdings aims to make a positive impact while servicing federal, state, local governments, and tribal entities.

501 - 1000 employees

🏛️ Government

🤝 B2B

🔒 Cybersecurity

📋 Description

• Conduct monthly fine-tuning of AI models based on customer usage and feedback. • Continuously monitor AI outputs for accuracy, fairness, and safety alignment. • Develop strategies for handling bias, hallucinations, and compliance issues in AI-generated results. • Collaborate with engineers to integrate refined models into production environments. • Perform weekly output refinement, including prompt engineering and embedding updates. • Design and maintain workflows for AI pipelines and evaluation benchmarks. • Ensure AI compliance with organizational, ethical, and regulatory standards (e.g., GDPR, SOC2, Responsible AI principles). • Leverage and optimize Azure AI services (OpenAI, Cognitive Search, Document AI, Vector DB, etc.). • Analyze datasets to extract insights, build predictive models, and support data-driven decision-making. • Design and execute experiments (A/B testing, model evaluation, statistical validation) to improve AI reliability and performance. • Design, manage, and optimize ETL pipelines for structured and unstructured data ingestion. • Work with big data platforms and Azure Data Lakes to ensure scalable storage, processing, and retrieval.

🎯 Requirements

• Strong background in Machine Learning, NLP, and Data Science. • Hands-on experience with Azure AI services (OpenAI, Azure AI Search, Cognitive Search, Document AI). • Proficient in Python for AI/ML development, automation, and data pipelines. • Practical experience with spaCy, Pandas, NumPy, PyTorch, and advanced text analytics. • Knowledge of embeddings, RAG pipelines, vector databases, and fine-tuning methodologies. • Strong foundation in statistical modeling, A/B testing, and data visualization. • Experience with ETL workflows, big data processing, and Azure Data Lakes. • Familiarity with compliance frameworks and AI governance best practices. • Strong analytical, problem-solving, and critical-thinking skills.