AI Engineer w​/Banking

AI Engineer W/ Banking

We need three AI Engineers (10+ Years) to design, build, and deploy machine learning and AI-driven solutions supporting the bank's technology and business initiatives. This role requires strong hands-on Python development skills combined with a solid understanding of banking/financial services environments — including data sensitivity, regulatory considerations, and enterprise system constraints. The position is on-site 5 days per week across East Lansing and Detroit offices.

Candidate must have strong, demonstrable Python development skills (production-level code, not just notebooks/scripting) as well as prior experience working within a bank or financial services institution — direct exposure to banking data, systems, and/or regulatory environment is required.

Experience with core ML/AI libraries and frameworks (e.g., PyTorch, Tensor Flow, scikit-learn, Hugging Face, Lang Chain, or similar)

Seeking an AI Engineer to design, build, and deploy machine learning and AI-driven solutions supporting the bank's technology and business initiatives. This role requires strong hands-on Python development skills combined with a solid understanding of banking/financial services environments — including data sensitivity, regulatory considerations, and enterprise system constraints. The position is on-site 5 days per week across East Lansing and Detroit offices.

This role is being engaged as a contract-to-hire, though the client is open to bringing on the right candidate as a full-time employee from day one.

• Design, develop, and deploy AI/ML models and pipelines to support banking operations, risk, fraud detection, underwriting, customer experience, or process automation use cases
• Write clean, production-grade Python code for data processing, model development, and integration with existing systems
• Collaborate with data engineering, IT, and business stakeholders to identify opportunities for AI/ML applications within a regulated banking environment
• Build and maintain data pipelines (ETL/ELT) to support model training and inference
• Evaluate, fine-tune, and deploy both traditional ML models and modern LLM/generative AI solutions where applicable
• Ensure models and AI systems meet banking industry standards for security, data privacy, and regulatory compliance
• Document model methodology, performance, and monitoring processes for internal governance and audit purposes
• Partner with IT infrastructure teams on deployment, scaling, and monitoring of AI solutions in production

• Strong, demonstrable Python development skills (production-level code, not just notebooks/scripting)
• Prior experience working within a bank or financial services institution — direct exposure to banking data, systems, and/or regulatory environment is required
• Experience with core ML/AI libraries and frameworks (e.g., PyTorch, Tensor Flow, scikit-learn, Hugging Face, Lang Chain, or similar)
• Solid understanding of data engineering fundamentals — SQL, data pipelines, cloud or on-prem data platforms
• Experience deploying models to production (MLOps practices, APIs, containerization a plus)
• Strong communication skills, with the ability to work cross-functionally with both technical and business teams
• Bachelor's degree in Computer Science, Data Science, Engineering, or related field (or equivalent practical experience)

• Experience with generative AI/LLM implementations in a regulated industry
• Familiarity with cloud platforms (Azure, AWS, or GCP)
• Exposure to model risk management or model governance frameworks common in banking
• Experience with core banking or lending platforms