Lead Machine Learning Engineer - MLOps
About The Position
We are seeking a highly skilled Machine Learning Engineer / MLOps Engineer to help scale and operationalize our cloud-based ML platform, with an immediate focus on managing and optimizing our AWS SageMaker environment. This role is ideal for someone with a strong foundation in machine learning who is passionate about building production-ready systems, designing robust pipelines, deploying infrastructure as a code, and enabling seamless model integration through APOs and data workflows. You will partner closely with data science teams to bridge the gap between experimentation and production, leveraging AWS services, serverless architectures, and modern CI/CD practices to deliver scalable, reliable, and efficient ML solutions. Perficient is the global AI and technology consulting firm disrupting the traditional consulting model. Powered by our 7,000+ advisors, engineers, and designers, Perficient implements AI-first solutions that break conventions and deliver outcomes that matter. Proudly serving clients that represent the world’s most innovative brands, and in collaboration with our powerful technology partner ecosystem, we bring deep industry expertise and data-driven design to redefine how businesses run and succeed. Perficient is different. For real. Learn more at perficient.com.
Requirements
- Strong foundation in machine learning.
- Experience building production-ready systems.
- Experience designing robust pipelines.
- Experience deploying infrastructure as code.
- Experience enabling seamless model integration through APOs and data workflows.
- Experience with AWS services.
- Experience with serverless architectures.
- Experience with modern CI/CD practices.
Responsibilities
- Scale and operationalize our cloud-based ML platform.
- Manage and optimize our AWS SageMaker environment.
- Build production-ready systems.
- Design robust pipelines.
- Deploy infrastructure as code.
- Enable seamless model integration through APOs and data workflows.
- Partner closely with data science teams to bridge the gap between experimentation and production.
- Leverage AWS services, serverless architectures, and modern CI/CD practices to deliver scalable, reliable, and efficient ML solutions.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
