AI/ML Specialist - AWS Focus

Key Responsibilities
Act as the AI/ML subject matter expert across teams, providing guidance, best practices, and hands-on support throughout the ML lifecycle.
Collaborate with data science and engineering teams to develop, deploy, and maintain ML models using AWS services such as SageMaker, Lambda, EKS, and Step Functions.
Architect and implement scalable, secure, and maintainable ML solutions in the AWS cloud environment using Infrastructure as Code (Terraform) and automation tools.
Support experimentation, tracking, and reproducibility using tools like MLflow.
Serve as a liaison between technical and non-technical teams, effectively communicating AI/ML strategies, timelines, and progress.
Contribute to CI/CD pipelines and ML operations using GitHub Actions and Python.
Apply Agile best practices in task management, sprint planning, and cross-functional collaboration.
(Bonus) Provide solution architecture support and input during project planning and review.

We are a company committed to creating inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity employer that believes everyone matters. Qualified candidates will receive consideration for employment opportunities without regard to race, religion, sex, age, marital status, national origin, sexual orientation, citizenship status, disability, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to Human Resources Request Form. The EEOC "Know Your Rights" Poster is available here.

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Required Skills & Qualifications
5+ years of experience in cloud engineering or DevOps with deep knowledge of AWS infrastructure and services.
Strong hands-on experience with machine learning operations (MLOps) in cloud environments.
Proficient with Terraform for Infrastructure as Code (IaC).
Experience with AWS ML services like SageMaker, Step Functions, EKS, and Lambda.
Familiarity with the end-to-end ML lifecycle: data ingestion, model training, evaluation, deployment, and monitoring.
Strong coding and automation skills using Python.
Hands-on experience with MLflow or similar model tracking platforms.
Proficient with GitHub, GitHub Actions, and Agile tools like Jira.
Excellent communication and stakeholder management skills.

Preferred Qualifications
AWS certifications, especially in Machine Learning or Solutions Architecture.
Experience in designing end-to-end cloud-native ML solutions.
Prior experience as a Solution Architect or working in an architecture-focused role.

Benefit packages for this role will start on the 31st day of employment and include medical, dental, and vision insurance, as well as HSA, FSA, and DCFSA account options, and 401k retirement account access with employer matching. Employees in this role are also entitled to paid sick leave and/or other paid time off as provided by applicable law.