DevOps Engineer

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Job description

We are CirrusLabs. Our vision is to become the world's most sought-after niche digital transformation company that helps customers realize value through innovation. Our mission is to co-create success with our customers, partners and community. Our goal is to enable employees to dream, grow and make things happen. We are committed to excellence. We are a dependable partner organization that delivers on commitments. We strive to maintain integrity with our employees and customers. Every action we take is driven by value. The core of who we are is through our well-knit teams and employees. You are the core of a values driven organization.

You have an entrepreneurial spirit. You enjoy working as a part of well-knit teams. You value the team over the individual. You welcome diversity at work and within the greater community. You aren't afraid to take risks. You appreciate a growth path with your leadership team that journeys how you can grow inside and outside of the organization. You thrive upon continuing education programs that your company sponsors to strengthen your skills and for you to become a thought leader ahead of the industry curve.

You are excited about creating change because your skills can help the greater good of every customer, industry and community. We are hiring a talented to join our team. If you're excited to be part of a winning team, CirrusLabs url removed is a great place to grow your career.

Job Title: DevOps Engineer (GCP, MLOps, Integration Experience)

Location: Hybrid (Atlanta, GA)

Employment Type: Conract

We are seeking a highly skilled DevOps Engineer with expertise in Google Cloud Platform (GCP), MLOps, and Terraform scripting to join our team in a hybrid role. As part of the DevOps team, you will be responsible for designing, developing, and maintaining cloud infrastructure and integration pipelines, particularly focused on Machine Learning Operations (MLOps) on the GCP platform.

Key Responsibilities:

Cloud Infrastructure Management:

Architect, implement, and maintain scalable and secure infrastructure on Google Cloud Platform (GCP) using Terraform scripts.

MLOps Pipeline Development:

Build and optimize MLOps pipelines for deploying machine learning models, ensuring seamless integration between data science teams and production environments.

Automation and CI/CD:

Develop and manage CI/CD pipelines, automation frameworks, and deployment processes for machine learning and other applications on GCP.

Integration Support:

Collaborate with cross-functional teams to integrate various tools, services, and APIs into the GCP environment, focusing on smooth data flows and model deployment.

Monitoring and Optimization:

Monitor system performance, troubleshoot issues, and implement proactive solutions to improve reliability, scalability, and efficiency.

Collaboration:

Work closely with data science, development, and operations teams to align DevOps processes with broader project goals and ensure the successful deployment of machine learning models and applications.

Qualifications:

Experience:

5+ years of experience as a DevOps Engineer with a focus on GCP and MLOps.

Proven experience in managing cloud infrastructure using Terraform for automation and infrastructure as code.

Strong background in setting up and managing MLOps pipelines on GCP for the deployment and lifecycle management of machine learning models.

Technical Skills:

Google Cloud Platform (GCP): Extensive experience with GCP services, including Compute Engine, Cloud Storage, AI/Client services, Kubernetes Engine, etc.

MLOps: Strong expertise in deploying and automating machine learning workflows, including experience with tools like Kubeflow, Vertex AI, or similar.

Infrastructure as Code (IaC): Advanced experience with Terraform for infrastructure provisioning and management on GCP.

CI/CD Pipelines: Experience with Jenkins, GitLab CI, CircleCI, or other CI/CD tools.

Containerization: Proficiency with Docker, Kubernetes, and container orchestration on GCP.

Soft Skills:

Strong problem-solving and troubleshooting abilities.

Excellent communication and teamwork skills, capable of working effectively in hybrid and cross-functional team environments.

Ability to manage competing priorities in a dynamic work setting.

Preferred Qualifications:

Certifications:

GCP Professional DevOps Engineer or GCP Professional Cloud Architect certification is preferred.

MLOps Tools:

Familiarity with TensorFlow Extended (TFX), MLflow, or similar MLOps frameworks is a plus.

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