Senior AI/ML Operations (MLOps) Engineer

Placements24; United States; Hybrid; USD 72.000 - 108.000; Vollzeit

Benefits dieser Stelle

Health insurance

PTO

Professional development

Remote or hybrid

Retirement plan

Team events

Zusammenfassung

Placements24 is seeking a Senior AI/ML Operations (MLOps) Engineer in Randburg, Gauteng, to bridge model development and production deployment. You will design end-to-end MLOps pipelines, automate builds, deployments, and monitoring, and collaborate with data scientists and ML engineers to streamline workflows.

The role requires 5+ years in software development, DevOps, or ML engineering, strong Python skills, and experience with AWS/Azure/GCP, Docker, Kubernetes, and CI/CD.

Qualifikationen

• Bachelor's or Master's degree in Computer Science, Engineering, or related field
• Minimum of 5 years of software development, DevOps, or ML engineering
• Proven experience implementing and managing MLOps pipelines and tools (MLflow, Kubeflow, SageMaker, Azure ML)
• Proficiency in Python scripting
• Experience with cloud platforms (AWS, Azure, GCP) and containers (Docker, Kubernetes)
• Solid understanding of CI/CD principles and tools (Jenkins, GitLab CI, GitHub Actions)
• Knowledge of ML concepts and the ML lifecycle
• Experience with monitoring and logging tools
• Strong problem-solving and communication skills

Aufgaben

• Design, implement, and manage end-to-end MLOps pipelines for ML models
• Automate build, testing, deployment, and monitoring of ML models in production
• Collaborate with data scientists to streamline model development workflows
• Manage infrastructure for ML training and inference on cloud or on-prem
• Develop tools to enhance ML operational efficiency and reliability
• Establish monitoring and alerting for ML models to detect drift
• Implement version control, testing, and CI/CD practices for ML projects
• Ensure security, scalability, and cost-effectiveness of ML infrastructure
• Document MLOps processes and best practices

Kenntnisse

Python

CI/CD

Docker

Kubernetes

MLflow

Kubeflow

Cloud platforms

Monitoring

Ausbildung

Bachelor's or Master's in CS/Engineering

Tools

AWS

Azure

GCP

Terraform

Ansible

Jobbeschreibung

About the Role

Our client, a dynamic tech firm at the forefront of AI innovation, is seeking a skilled Senior AI/ML Operations (MLOps) Engineer to enhance their machine learning capabilities in Randburg, Gauteng. This role is critical in bridging the gap between machine learning model development and production deployment, ensuring that our AI solutions are scalable, reliable, and efficient. You will be responsible for building and maintaining robust MLOps pipelines, automating workflows, and implementing best practices for continuous integration, delivery, and monitoring of ML models. This is an excellent opportunity to work with cutting-edge technologies, collaborate with talented data scientists and engineers, and make a significant impact on the operational excellence of our AI initiatives. We are looking for a candidate with a strong background in software engineering, DevOps principles, and a deep understanding of the machine learning lifecycle. Your expertise in **Randburg** will be key to streamlining our AI development and deployment processes.

Key Responsibilities

• Design, implement, and manage end-to-end MLOps pipelines for machine learning models.
• Automate the build, testing, deployment, and monitoring of ML models in production environments.
• Collaborate closely with data scientists and ML engineers to streamline model development workflows.
• Implement and manage infrastructure for ML training and inference, utilizing cloud platforms (AWS, Azure, GCP) or on-premises solutions.
• Develop tools and scripts to enhance ML operational efficiency and reliability.
• Establish monitoring and alerting systems for ML models to ensure performance and detect drift.
• Implement version control, testing, and CI/CD practices for machine learning projects.
• Ensure security, scalability, and cost-effectiveness of ML infrastructure.
• Stay up-to-date with the latest MLOps tools, technologies, and best practices.
• Document MLOps processes, infrastructure, and best practices.

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• Minimum of 5 years of experience in software development, DevOps, or ML engineering.
• Proven experience implementing and managing MLOps pipelines and tools (e.g., MLflow, Kubeflow, SageMaker, Azure ML).
• Proficiency in scripting languages such as Python.
• Experience with cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes).
• Solid understanding of CI/CD principles and tools (e.g., Jenkins, GitLab CI, GitHub Actions).
• Knowledge of machine learning concepts and the ML lifecycle.
• Experience with monitoring and logging tools.
• Strong problem-solving and analytical skills.
• Excellent communication and collaboration abilities.
• Familiarity with infrastructure as code tools (e.g., Terraform, Ansible) is a plus.

Benefits

• Competitive salary and attractive performance-based bonus.
• Comprehensive health, dental, and vision insurance.
• Generous paid time off and holiday schedule.
• Professional development opportunities, including training, workshops, and conference attendance.
• Access to modern technology and collaborative tools.
• Dynamic and innovative work culture.
• Retirement savings plan with company contributions.
• Employee assistance program.
• Regular social events and team-building activities.
• Support for remote or hybrid work arrangements.