AI Engineer Role in Machine Learning and Artificial Intelligence (Industry, Contract) Sage IT in United States

Sage IT is currently hiring for an AI Engineer role based in Dallas, TX or Charlotte, NC on a contract basis. This position is ideal for experienced professionals with a strong background in machine learning, deep learning, and generative AI. The successful candidate will be responsible for designing, building, and deploying scalable machine learning models and AI systems that drive business impact. Key responsibilities include developing production-grade ML models using frameworks such as TensorFlow, PyTorch, or Hugging Face, building and optimizing data pipelines and MLOps workflows, and leading AI feature development including model fine-tuning, RAG pipelines, and agentic systems.

The role also involves model evaluation, A/B testing, performance tuning, and integrating AI into microservices, APIs, and real-time applications. Mentoring junior engineers and contributing to technical roadmaps and best practices are also part of the job. Candidates must have at least a Bachelor's or Master's degree in Computer Science, AI, or a related field, with a PhD preferred. A minimum of 8 years of experience in AI/ML engineering with proven production deployments is required. Expertise in Python, data structures, algorithms, and cloud platforms (AWS, Azure, GCP) is essential, along with deep experience in ML frameworks (TensorFlow, PyTorch, Scikit-learn) and vector databases. Hands-on experience with LLMs, prompt engineering, RAG, and deployment tools (Docker, Kubernetes) is also necessary.

Preferred skills include experience in regulated domains such as fintech or healthcare, contributions to open-source AI projects or publications, and familiarity with LangChain, Vertex AI, or Bedrock. This is a contract-based industry position and does not offer academic funding or scholarships. Compensation details are not specified. Interested candidates should send their resume to [email protected] or contact the provided phone number. For more information, visit the LinkedIn profile of the recruiter or the job posting link provided.