Senior AI/ML Engineer

Position Overview

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.

Responsibilities

Model Development & Optimization

• 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

AI Solution Delivery & Operationalization

• 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

Data & Analytics Engineering Alignment

• 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

Governance, Standards & Responsible AI

• 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

Cross-Functional Collaboration

• 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

Mentorship & Technical Leadership

• 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

Minimum 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

Additional Requirements

• 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)

Desired Skills

• 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