AI Engineer

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 required on a resume and for submittal:
1. How many years working with: AI Engineer
2. How many years working with: Python
3. How many years working with: LLM
4. How many years working with: Banking or Financial Services
5. How many years working with: ML/AI libraries and frameworks (e.g., PyTorch, TensorFlow, scikit-learn, Hugging Face, LangChain, or similar)

Job Description:
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