Senior AI/ML Engineer

International Motors, LLC•Lisle, IL

About The Position

The Senior AI/ML Engineer is responsible for designing, developing, and deploying scalable machine learning and AI solutions that deliver measurable business value. This role operates as a key contributor within the AI/ML function, translating business requirements into production-ready models and solutions while ensuring alignment with enterprise AI standards, architecture, and governance frameworks. The Senior AI/ML Engineer collaborates closely with cross-functional teams across data engineering, analytics, and business domains to enable end-to-end AI solution delivery within a federated AI Center of Excellence (COE) model.

Requirements

Bachelor's degree and at least 1 year of software engineering experience OR Master's degree and no experience OR At least 3 years of software engineering experience
Qualified candidates, excluding current employees, must be legally authorized on an unrestricted basis (US Citizen, Legal Permanent Resident, Refugee or Asylee) to be employed in the United States.
We do not anticipate providing employment related work sponsorship for this position (e.g., H-1B status)

Nice To Haves

Master’s degree in a quantitative or technical field
Strong proficiency in Python and ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch)
Experience with model deployment and MLOps practices
Experience working with cloud-based AI/ML platforms and data ecosystems
Familiarity with enterprise data architectures and distributed data processing
Experience working in cross-functional and enterprise environments
Independently delivers end-to-end AI/ML solutions that scale in production
Consistently applies enterprise standards, governance, and best practices
Effectively collaborates across business and technical teams
Enables junior team members through mentorship and guidance
Contributes reusable assets and patterns that accelerate AI delivery

Responsibilities

Design, build, and deploy machine learning models for complex business use cases
Lead feature engineering, model selection, tuning, and validation processes
Ensure models are scalable, reusable, and aligned to enterprise standards
Apply advanced techniques (e.g., ensemble models, optimization strategies) where appropriate
Own end-to-end delivery of AI/ML solutions from concept through production deployment
Collaborate with data engineering teams to integrate models into production pipelines
Implement and maintain model lifecycle management practices (deployment, monitoring, retraining)
Ensure solutions meet performance, reliability, and scalability requirements
Work with large-scale structured and unstructured data to support ML development
Partner with data engineering teams to define data requirements and improve data quality
Contribute to development of data pipelines and curated data assets for AI use cases
Support integration with enterprise analytics and BI solutions
Ensure adherence to enterprise AI governance, security, and compliance standards
Apply responsible AI practices, including documentation, explainability, and risk considerations
Contribute to development and refinement of AI/ML best practices and reusable patterns
Support model documentation and auditability requirements
Partner with business stakeholders to translate use cases into technical solutions
Collaborate with data scientists, analysts, and engineers across domains (e.g., Service, R&D, finance)
Contribute to AI use case intake, evaluation, and prioritization processes
Communicate technical findings and model outputs to both technical and non-technical audiences
Provide guidance and mentorship to junior AI/ML engineers and data scientists
Review code, models, and technical designs to ensure quality and consistency
Promote adoption of best practices in model development and deployment
Act as a technical SME within project teams