AI Engineer

Kforce has a client in Houston, TX in need of an AI Engineer to play a critical role in designing, training, and deploying advanced machine learning and generative AI solutions that address complex, real-world challenges. You will be working on cutting-edge AI initiatives, large language models (LLMs), agentic workflows, and multimodal systems, delivering impactful and responsible AI applications at enterprise scale. This is a hybrid role which requires 3 days onsite, 2 days remote in Houston, TX.Responsibilities:Design, develop, and train machine learning and deep learning models for production useBuild agentic AI systems, including multi-step reasoning workflows, tool using agents, and autonomous or semi-autonomous processesEvaluate, customize, and fine-tune open-source and commercial large language models (LLMs) for domain-specific use casesDevelop impactful AI applications that deliver measurable business and operational valueDesign robust ML systems capable of handling multimodal data (text, tabular data, images, documents, etc.)Apply advanced statistical analysis and machine learning techniques to large, complex datasetsLeverage state-of-the-art Generative AI techniques such as Retrieval Augmented Generation (RAG), prompt engineering, embeddings, and model orchestrationLead the design and implementation of AI solutions leveraging Microsoft AI and Azure services, and open-source LLM models (e.g. HuggingFace, etc.)Collaborate closely with product managers, domain experts, data engineers, and software engineers to define and deliver AI-driven solutionsParticipate in fast-paced proof-of-concepts (POCs) and pilots to validate solution designsEnsure best practices for MLOps, including CI/CD, monitoring, versioning, and lifecycle management* Bachelor's degree in Computer Science, Mathematics, Engineering, Data Science, or a related field (Master's or PhD preferred)Proven experience as a Machine Learning Engineer, AI Engineer, or similar senior-level roleStrong foundation in mathematics, probability, statistics, and algorithmsDemonstrated experience training and deploying machine learning and deep learning modelsExpertise in Python and experience with production-quality codebases (experience with C#, Java, or similar languages is a plus)Hands-on experience with deep learning frameworks such as PyTorch, TensorFlow, or KerasStrong experience working with language foundation models and techniques for adapting them to specific use cases (fine-tuning, prompt engineering, RAG, evaluation)Experience working with both open-source LLMs (e.g., LLaMA, Mistral, Falcon) and commercial LLM platformsFamiliarity with CI/CD practices across the model lifecycleSolid understanding of software architecture, data structures, and data modelingExcellent communication skills with the ability to explain complex technical concepts to diverse audiencesStrong analytical thinking and problem-solving skillsAbility to work effectively in cross-functional, collaborative teamsNice to have:Experience designing, building, and maintaining AI solutions on commercial cloud platforms, especially Microsoft AzureHands-on experience with Azure AI services, Azure Machine Learning, or similar platformsStrong knowledge of MLOps and DevOps tools such as Azure DevOps, GitHub Actions, or GitLabExperience with data engineering and end-to-end data science workflowsFamiliarity with responsible AI practices, model governance, and risk managementExperience delivering AI solutions in regulated or mission-critical environmentsPassion for continuous learning and staying at the forefront of AI and machine learning advancements