AI Summary
Join our talent network and connect with U.S. clients for flexible, project-based development work as an MLOps Engineer. You will integrate directly into our client's team and work alongside their existing designers and engineers on a daily basis. We're looking for a highly skilled MLOps Engineer with 4+ years of experience in MLOps, Machine Learning Engineering, or DevOps focused on AI infrastructure.
Key Highlights
4+ years of professional experience in MLOps, Machine Learning Engineering, or DevOps focused on AI infrastructure
Advanced English is required
Successful completion of a four-year college degree is required
Key Responsibilities
Integrate directly into our client's team and work alongside their existing designers and engineers on a daily basis
Design and maintain scalable, reliable AI infrastructure on cloud platforms such as AWS, GCP, or Azure
Work through new and difficult issues and contribute to libraries as needed
Technical Skills Required
Benefits & Perks
Competitive pay
100% remote work
The ability to work with leading startups and Fortune 500 companies
Continuing education opportunities
Opportunity to grow and expand your career
Job Description
About FullStack
FullStack is the most transparent IT talent network, connecting highly skilled individuals with top global companies and Silicon Valley startups for remote, on-demand projects. We focus on building a trusted, high-performance network where talent can thrive in a positive, respectful, and supportive environment. By prioritizing transparency, fair opportunities, and professional growth, we empower our engineers to deliver their best work while collaborating with innovative teams worldwide.
We’re Most Proud Of
- Offering life-changing opportunities for talented software professionals across the Americas.
- Enhancing highly-skilled software development teams of hundreds of the world’s greatest companies.
- Our 4.2-star rating on GlassDoor.
- Our client Net Promoter Score of 68, twice the industry average.
Join our talent network and connect with U.S. clients for flexible, project-based development work as an MLOps Engineer.
- You will integrate directly into our client's team and work alongside their existing designers and engineers on a daily basis.
Interested in remote work opportunities in Devops? Discover Devops Remote Jobs featuring exclusive positions from top companies that offer flexible work arrangements.
- 4+ years of professional experience in MLOps, Machine Learning Engineering, or DevOps focused on AI infrastructure.
- Advanced English is required.
- Successful completion of a four-year college degree is required.
- Proven experience in automation of ML lifecycles with CI/CD and Continuous Training (CT) pipelines.
- Deep understanding of large language models (LLMs), prompt engineering, and the latest trends in generative AI.
- Hands-on experience in deployment and orchestration using Docker and Kubernetes (Kubeflow, Seldon, or KServe).
- Solid experience in the implementation of model monitoring for drift, latency, and performance (Prometheus, Grafana).
- Ability to design and maintain scalable, reliable AI infrastructure on cloud platforms such as AWS, GCP, or Azure.
- Ability to work through new and difficult issues and contribute to libraries as needed.
- Ability to create and maintain continuous integration and delivery of applications.
- Forensic attention to detail.
- A positive mindset and a can-do attitude.
- Experience working on Agile / Scrum teams.
- Meaningful experience working on large, complex systems.
- Ability to take extreme ownership over your work. Every day is a challenge to ensure you are performing to the expectations you and your team have agreed upon.
- Ability to identify with the goals of FullStack's clients, and dedicate yourself to delivering on the commitments you and your team make to them.
- Ability to consistently work 40 hours per week.
Browse our curated collection of remote jobs across all categories and industries, featuring positions from top companies worldwide.
- Competitive pay.
- 100% remote work.
- The ability to work with leading startups and Fortune 500 companies.
- Continuing education opportunities.
- Opportunity to grow and expand your career.
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