MLOps Engineer

Requirement ID: 91652-1
Location: Sunnyvale, CA (Hybrid role)
Duration: 6 months
Job Title: MLOps Engineer
Pay Rate: $50 - $56/hr

Requirement ID: 91652-1
Location: Sunnyvale, CA (Hybrid role)
Duration: 6 months
Job Title: MLOps
Pay Rate: $50 - $56/hr
We are seeking an experienced MLOps Engineer with a strong background in AI/ML, DevOps, Cloud Infrastructure, and CI/CD automation . The ideal candidate will be responsible for building, deploying, monitoring, and maintaining scalable machine learning platforms and production environments. This role requires expertise in automating ML workflows, infrastructure provisioning, container orchestration, and cloud-native technologies to ensure reliable and efficient model deployment and operations.

Key Responsibilities

• Design, implement, and maintain end-to-end MLOps and CI/CD pipelines for machine learning applications and platforms.
• Automate model training, testing, deployment, and monitoring processes across multiple environments.
• Collaborate with Data Scientists, ML Engineers, and Development teams to operationalize AI/ML solutions.
• Build and manage containerized applications using Docker and orchestrate deployments through Kubernetes .
• Develop and maintain Infrastructure as Code (IaC) solutions for scalable and repeatable deployments.
• Manage and optimize cloud-based infrastructure on AWS and other cloud platforms.
• Implement monitoring, logging, and alerting solutions using Prometheus, Grafana, ELK Stack , and related tools.
• Ensure system reliability, availability, performance, and security through proactive monitoring and automation.
• Troubleshoot production issues, optimize deployment processes, and implement automated recovery solutions.
• Conduct system testing, security assessments, and performance tuning activities.
• Drive DevOps best practices, release management processes, and continuous improvement initiatives.

Required Skills & Qualifications

• 8-10 years of experience in DevOps, MLOps, Cloud Engineering, or Platform Engineering .
• Hands-on experience with AI/ML model deployment and operationalization .
• Strong expertise in CI/CD tools such as Jenkins, GitHub Actions, GitLab CI/CD , or similar platforms.
• Extensive experience with Docker and Kubernetes .
• Strong cloud experience with AWS and cloud-native services.
• Proficiency in Infrastructure as Code (Terraform, CloudFormation, Ansible, etc.) .
• Experience with monitoring and observability tools including Prometheus, Grafana, ELK Stack .
• Strong scripting and automation skills using Python, Shell Scripting, and Groovy .
• Experience with version control systems such as Git/GitHub .
• Knowledge of security, networking, and high-availability architectures.
• Strong troubleshooting, analytical, and problem-solving abilities.

Preferred Qualifications

• Experience with ML platforms such as SageMaker, Kubeflow, MLflow, Vertex AI, or Databricks .
• Familiarity with model governance, feature stores, and model monitoring frameworks.
• Experience with Agile/Scrum methodologies.
• Cloud certifications (AWS, Kubernetes, DevOps) are a plus.

• Company Benefits & Culture
• Competitive salary and benefits package
• Supportive and collaborative work environment
• For immediate consideration please click APPLY to begin the screening process with Alex.
• Opportunities for professional growth and development