CodeRoad
Technology
MachineLearningOperationsEngineer(MLOps)
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Machine Learning Operations Engineer (MLOps) at CodeRoad. Skills: MLOps, Agentic AI, Cloud Infrastructure, Automation. Design deployment pipelines. Implement deployment pipelines”
Industry & Context.
Troubleshooting
What They're Looking For.
Must Have
4+ years MLOps experience, 1+ year AI/ML production deployment, 4 years GCP or AWS experience, 1+ year MLOps tools experience, Python expertise, Git experience, Monitoring tools experience, Security principles understanding, Ethical AI principles understanding, Bachelor's degree
Nice to Have
Agentic AI systems experience, Advanced degrees, MLOps certifications, AI/ML certifications, Cloud technologies certifications
What You'll Do.
Design deployment pipelines
Implement deployment pipelines
Build cloud infrastructure
Maintain cloud infrastructure
Develop automated workflows
Maintain automated workflows
Implement monitoring systems
Manage monitoring systems
Track model performance
Track decision-making accuracy
Integrate security best practices
Ensure AI system compliance
Work with AI researchers
Work with data scientists
Work with software engineers
Work with product teams
Align MLOps processes
Facilitate iterative development
Facilitate iterative deployment
Establish governance frameworks
Enforce governance frameworks
How You'll Work.
Team & Collaboration
Cross-functional teams; AI researchers; Data scientists; Software engineers; Product teams
Communication Scope
Explain technical concepts
Process & Methodology
CI/CD, CT
Full Job Description
Machine Learning Operations (MLOps) Engineer The Team At Coderoad, we're more than just a software development company—we're your gateway to the global tech world. Whether you're looking to skill up or level up your career, we offer the challenges you’ve been searching for. We provide end-to-end software development services and give you the opportunity to work on exciting, real-world projects in a supportive environment. Whether it's staff augmentation, dedicated IT teams, or general software engineering, we have opportunities for everyone to challenge themselves and take their career to the next level! Position Location - Latam (Remote). Time Zone Requirements - This team operates on the East/West Coast time zones. About the Role We are seeking a skilled and innovative Machine Learning Operations (MLOps) Engineer with a focus on Agentic AI to design, deploy, and maintain scalable, robust, and ethical autonomous AI systems. The ideal candidate will combine deep expertise in modern MLOps practices with a solid understanding of agentic AI principles, enabling the seamless integration, monitoring, and optimization of AI models that exhibit autonomous decision-making and adaptability. You will be a key contributor in our cross-functional teams, ensuring our agentic AI solutions are reliable, efficient, and aligned with our business goals and ethical standards. Key Responsibilities Model Deployment & Integration: Design and implement scalable, secure, and production-grade pipelines for deploying agentic AI models. Focus on seamless integration with existing systems and enable real-time adaptability for autonomous decision-making. Cloud Infrastructure Management: Build and maintain robust cloud infrastructure on Google Cloud Platform (GCP) or Amazon Web Services (AWS) for the entire AI lifecycle. Leverage services like GCP's Vertex AI and Cloud Functions, or their AWS equivalents such as Amazon SageMaker, and AWS Lambda, to create efficient and resilient environments. Au
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