AI / ML Engineer

Phaedon•Minneapolis, MN

137d•Hybrid

About The Position

This is an excellent opportunity for an innovator and problem solver who thrives at the intersection of AI, cloud engineering, and product development. We are seeking an AI/ML Engineer to join our analytics and product development team. You will be a key member of our team, responsible for building, deploying, and scaling AI-powered data products and analytics solutions that solve real client challenges. At Phaedon, we recognize that exceptional talent comes with diverse experiences. The final title and compensation will be thoughtfully determined using factors including but not limited to relevant work experience, skills, certifications and competencies that align to the specified role.

Requirements

Bachelor's degree in data science, computer science, computer engineering, or related field
5+ years of hands-on experience in relevant skillsets including Python development and cloud engineering
Strong experience with AWS services, particularly Bedrock, SageMaker, Lambda, Glue, and Athena
Proficiency in AI implementation, model deployment, and productionalization
Proven experience of authoring product requirement documents, user workflows, and technical flows
Knowledge of Infrastructure-as-Code (Terraform, CloudFormation)
Experience with source control, automated deployment pipelines (Git, Docker)
Proven experience building and deploying ML models with various methodologies
Client-facing experience in analytics or consulting environment
Strong presentation and communication skills for technical and non-technical audiences
Programming: Advanced Python (including AI/ML libraries like transformers, langchain), SQL, Boto3
AI/ML Tools: AWS Bedrock, SageMaker, prompt engineering, model fine-tuning
Cloud Services: AWS ecosystem with focus on data and AI services
Visualization: Experience with Tableau, PowerBI, or QuickSight
Development Practices: Object-oriented programming, testing frameworks, CI/CD

Nice To Haves

Experience with vector databases and RAG implementations
Knowledge of LLM fine-tuning and deployment strategies
Familiarity with MLOps practices and model versioning
Experience with API development and microservices architecture
Background in professional services or consulting environments
Experience with AWS data lake tools and architecture
Previous experience in client service roles within analytics or technology consulting

Responsibilities

Design, build, and deploy AI-powered data products and analytics solutions using cutting-edge technologies
Implement and productionalize AI/ML models using AWS Bedrock and other AI services
Transform proof-of-concept work into robust, production-ready systems
Develop RAG (Retrieval-Augmented Generation) systems for AI applications
Build cloud-native applications with focus on scalability, reliability, and performance
Work directly with clients to understand business requirements and translate them into product requirements and technical solutions
Present product requirements, user flows, and technical findings and recommendations to client stakeholders with clarity and professionalism
Conduct exploratory data analysis and deliver actionable insights through clear visualizations and reports
Collaborate with client teams to ensure successful implementation and adoption of analytics solutions
Architect and maintain data lake solutions using AWS native tools including Lake Formation, Glue, and Athena
Develop automation and monitoring solutions using Lambda and other AWS services
Create and maintain Infrastructure-as-Code (IAC) using Terraform, Pulumi and CloudFormation
Build data pipelines that synthesize complex datasets from multiple sources into actionable insights
Implement error-proofing strategies and robust testing frameworks including integration testing
Develop CI/CD pipelines for automated deployment and model versioning
Create monitoring and logging solutions for production AI systems
Ensure security best practices for AI applications and data handling