Python AI Engineer

Job Description

AI Engineer/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, TensorFlow, scikit-learn, Hugging Face, LangChain, 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.

Key Responsibilities

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

Required Qualifications

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, TensorFlow, scikit-learn, Hugging Face, LangChain, 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)

Preferred Qualifications

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 Logistics