Senior Machine Learning Operations (MLOps) Engineer

Placements24; Riverton (UT); Remote; USD 140,000 - 190,000; Full time

Benefits offered by this job

Competitive salary

Health, dental, and vision insurance

Retirement contributions

Paid time off

Professional development budgets

Fully remote work

Job summary

Placements24 is seeking a Senior MLOps Engineer to design and maintain scalable ML infrastructure, pipelines, and model-serving platforms. You will bridge data science and IT operations, delivering reliable ML systems in a fully remote setup.

You will implement CI/CD for ML, manage cloud resources, containerize with Docker/Kubernetes, apply IaC (Terraform/Ansible), and collaborate with data scientists and software engineers to accelerate deployment and monitoring.

Qualifications

• 5+ years in software engineering or DevOps with focus on MLOps or cloud infra for ML.
• Proficiency in Python and Bash scripting.
• Hands-on cloud experience with AWS, Azure or GCP.
• Expertise with Docker, Kubernetes and IaC tools (Terraform/Ansible).
• Strong problem-solving and communication skills.

Responsibilities

• Design, implement, and manage robust CI/CD pipelines for ML models.
• Develop and maintain scalable infra for training, deployment, and serving ML models.
• Implement monitoring, logging, and alerting for ML in production.
• Automate ML lifecycle: data validation, model training, testing, deployment.
• Collaborate with data scientists and engineers to streamline ML development and deployment.
• Ensure reliability, scalability, and security of ML systems and infra.
• Manage and optimize cloud resources (AWS/Azure/GCP) for ML workloads.
• Troubleshoot ML model performance and infra issues.
• Stay current with emerging MLOps tools, technologies, and best practices.

Skills

Python programming

CI/CD expertise

Cloud infrastructure design

Education

Bachelor's degree in Computer Science or related field

Master's degree (preferred)

Tools

Docker

Kubernetes

Terraform

Ansible

AWS

Azure

GCP

TensorFlow Serving

Seldon Core

GitHub Actions

Jenkins

Job description

About the Role

Our client, a pioneering force in AI-driven analytics, is seeking a highly skilled Senior Machine Learning Operations (MLOps) Engineer to join their dynamic and fully remote team. This role is essential for building and maintaining the infrastructure and processes required to deploy, monitor, and manage machine learning models at scale. You will bridge the gap between data science and IT operations, ensuring seamless integration and efficient performance of ML systems. The ideal candidate has a robust background in software engineering, cloud infrastructure, and a deep understanding of the machine learning lifecycle. This is an exceptional opportunity to drive operational excellence in AI and contribute to innovative projects from anywhere, supporting our clients' advanced analytical capabilities.

Key Responsibilities

• Design, implement, and manage robust CI/CD pipelines for machine learning models.
• Develop and maintain scalable infrastructure for training, deploying, and serving ML models.
• Implement monitoring, logging, and alerting systems for ML models in production.
• Automate the ML lifecycle, including data validation, model training, testing, and deployment.
• Collaborate with data scientists and software engineers to streamline the ML development and deployment process.
• Ensure the reliability, scalability, and security of ML systems and infrastructure.
• Manage and optimize cloud resources (e.g., AWS, Azure, GCP) for ML workloads.
• Troubleshoot and resolve issues related to ML model performance and infrastructure.
• Stay current with emerging MLOps tools, technologies, and best practices.

Requirements

• Bachelor's degree in Computer Science, Engineering, or a related field; Master's degree is a plus.
• 5+ years of experience in software engineering or DevOps, with at least 3 years focused on MLOps or cloud infrastructure for ML.
• Proficiency in programming languages such as Python and experience with scripting languages (e.g., Bash).
• Hands-on experience with cloud platforms (AWS, Azure, or GCP) and their relevant ML services.
• Expertise in containerization technologies (Docker, Kubernetes).
• Experience with CI/CD tools (e.g., Jenkins, GitLab CI, GitHub Actions).
• Familiarity with ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and ML model serving technologies (e.g., TensorFlow Serving, Seldon Core).
• Strong understanding of infrastructure as code (IaC) principles and tools (e.g., Terraform, Ansible).
• Excellent problem-solving and communication skills.

Benefits

Our client offers a highly competitive salary, comprehensive health, dental, and vision insurance, generous retirement contributions, and ample paid time off. This fully remote position provides the ultimate flexibility. We invest in our employees' professional development through access to online courses, training programs, and conference attendance budgets. You will work with cutting-edge technologies and contribute to impactful AI projects in a collaborative, innovation-driven environment. Our client values a healthy work-life balance and fosters a culture of continuous learning and growth, making this an ideal opportunity for an experienced MLOps engineer.