We’re looking for a seasoned cloud and machine learning expert who thrives at the intersection of AWS, DevOps, and scalable ML platforms . If you enjoy building modern, production-grade ML systems and shaping cloud transformation strategies, this role is for you.
What You’ll Bring
- 10+ years of overall experience , including 7+ years leading AWS cloud transformation and DevOps initiatives
- Deep expertise in building and managing end-to-end machine learning lifecycles using Amazon SageMaker
- Proven ability to design, deploy, and optimize CI/CD pipelines for ML workflows , including model containerization with Docker and deployment via SageMaker endpoints
- Strong experience in monitoring model performance, ensuring model health, and maintaining robust, scalable infrastructure
- Solid understanding of data governance, security, and compliance in cloud-based ML environments
What You’ll Do
- Architect and implement production-grade ML platforms on AWS
- Establish best practices for ML Ops, CI/CD, and automated deployments
- Drive observability, reliability, and performance improvements across hybrid cloud ecosystems
- Define and manage persona-based access controls using SageMaker Role Manager
- Set up and manage SageMaker Studio domains, user profiles, and secure VPC configurations
What Makes You Stand Out
- 5+ years of AWS architecture experience
- AWS Solutions Architect Certification
- Strong grasp of DevOps, SRE principles, and modern observability tools
Base Compensation Range: $125,000-140,000
The posted range is the hiring range for this role — a subset of the broader range available to employees over time — and reflects base salary across our national hiring scale. Final offers are based on several factors, including the candidate's skills and experience, internal pay equity, work location, market conditions for the role, and the specific scope and responsibilities of the position. The top of the range is reserved for candidates who notably exceed the requirements; the lower end applies to those with less experience or fewer preferred qualifications. For positions based in higher-cost zones (e.g., California, New York, New Jersey), actual compensation may exceed the posted range; your recruiter will share specifics during the process.