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DevOps MLOps Engineer

We are seeking a skilled and versatile DevOps/MLOps Engineer to join our team and lead IT operations. This hybrid role involves ensuring seamless integration and deployment of applications while maintaining a robust, high-performance IT infrastructure.

As a DevOps/MLOps Engineer, you will focus on scalable and secure systems, optimized for accelerated computing and deep learning workloads. Knowledge of SysOps and SecOps is considered an advantage.

Key Responsibilities

  • Manage GPU/CPU infrastructure for cloud and on-premise environments.
  • Assist with the setup and monitoring of ML pipelines.
  • Design and maintain CI/CD pipelines and automation solutions.
  • Develop and maintain backup and disaster recovery solutions to ensure data integrity.
  • Document system architecture and processes to streamline operations and audits.
  • Collaborate with ML and software engineers to meet deployment requirements.

Required:

  • 3+ years of hands-on experience in DevOps and/or MLOps roles.
  • Expertise in Linux systems and GPU/CPU cluster management.
  • Strong scripting skills (e.g., Python, Bash).
  • Experience with CI/CD workflows (e.g., GitHub Actions).
  • Experience with ML frameworks (e.g., TensorFlow, PyTorch).
  • Knowledge of containerization technologies (e.g., Docker, Kubernetes).
  • Fluent English communication skills.

Plus:

  • Familiarity with infrastructure automation tools (e.g., Ansible, Terraform).
  • Familiarity with monitoring and log analysis tools (e.g., ELK, Grafana, Prometheus).
  • Understanding of SecOps principles to enhance security in CI/CD and cloud infrastructure.
  • Be a part of an international company that is at the forefront of financial technology innovation.
  • Benefit from a competitive compensation package:
    • Competitive salary (2000 - 2500 EUR NET depending on qualifications)
    • Bonus based on transparent AI2C's profit sharing plan
  • Comprehensive health insurance fully paid by the company
  • Use of top of the line cloud-based GPU computing and technologies
  • Hybrid working environment.
  • Be part of a dynamic team with open-minded and inclusive company culture.
  • A collaborative environment where creativity and innovation are encouraged.

Average salary estimate

$27000 / YEARLY (est.)
min
max
$24000K
$30000K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

What You Should Know About DevOps MLOps Engineer, Ai2C Technologies

Are you ready to take your career to the next level? Join us as a DevOps MLOps Engineer at an innovative financial technology company where your skills will be put to the test! In this hybrid role, you’ll not only manage high-performance IT infrastructure but also integrate and deploy applications seamlessly. We’re looking for someone who has a knack for creating scalable and secure systems, especially optimized for deep learning workloads. With over three years of hands-on experience in the DevOps/MLOps domain, you’ll be in charge of managing GPU and CPU infrastructures across cloud and on-premise environments. Your expertise in CI/CD workflows, complemented by strong scripting skills, will guide you in designing and maintaining efficient automation solutions. You’ll collaborate with talented ML and software engineers while documenting critical system processes to ensure everything runs smoothly. While knowledge of SysOps and SecOps are a plus, what’s most important is your passion for innovation and your eagerness to contribute to a dynamic team environment. The competitive compensation package includes a great salary, a profit-sharing bonus plan, and comprehensive health insurance fully covered by us! If you're looking to work in an inclusive culture that fosters creativity, you’ll love being part of our team. Let’s drive positive change together!

Frequently Asked Questions (FAQs) for DevOps MLOps Engineer Role at Ai2C Technologies
What are the key responsibilities of a DevOps MLOps Engineer at this company?

As a DevOps MLOps Engineer at our company, you'll manage both GPU and CPU infrastructures, assist with ML pipeline setup, and design CI/CD pipelines. You’ll also document system architectures and collaborate with ML and software engineers to ensure all deployment requirements are met. It’s an exciting role that blends operational excellence with cutting-edge technology.

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What qualifications are required for the DevOps MLOps Engineer position?

To qualify for the DevOps MLOps Engineer position, candidates should have over three years of hands-on experience in DevOps or MLOps roles. It’s essential to be skilled in Linux systems, cluster management, and CI/CD workflows. Strong scripting abilities in languages like Python or Bash and familiarity with ML frameworks such as TensorFlow or PyTorch are also crucial.

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Is prior experience in SysOps and SecOps beneficial for the DevOps MLOps Engineer role?

Yes, prior experience in SysOps and SecOps is definitely beneficial for the DevOps MLOps Engineer role. While it's not mandatory, having a solid understanding of these areas can enhance your ability to manage security and operations effectively, especially in CI/CD and cloud infrastructures.

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What benefits does the company offer for the DevOps MLOps Engineer position?

The company offers a competitive compensation package, including a salary ranging from 2000 to 2500 EUR NET based on qualifications. Additional benefits include a transparent profit-sharing bonus plan, comprehensive health insurance, and the opportunity to work with state-of-the-art cloud-based computing technologies in a hybrid environment.

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What is the work culture like for a DevOps MLOps Engineer in this company?

The work culture here is dynamic and inclusive, emphasizing open-minded collaboration. As a DevOps MLOps Engineer, you’ll be encouraged to share your creativity and innovate within a supportive team that values every member's contribution to our projects and overall mission.

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Common Interview Questions for DevOps MLOps Engineer
Can you explain your experience with CI/CD workflows as a DevOps MLOps Engineer?

Certainly! In your answer, discuss specific CI/CD tools you've used, such as GitHub Actions or others, detailing how you've implemented them in previous projects. Share examples of how you've optimized deployment processes and ensured reliability in production environments.

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What is your approach to managing GPU and CPU infrastructures?

Focus on discussing your hands-on experience managing server infrastructures, emphasizing key tools and technologies leveraged. Provide examples of how you've ensured scalability and performance in your setups, particularly with respect to workloads that demand high computational power.

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How do you ensure the security of CI/CD pipelines?

Speak about your knowledge in SecOps principles and describe strategies you've employed, such as using automated security scanning tools during the build process or ensuring proper access controls are in place. Highlight any instances where you've mitigated security vulnerabilities.

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What scripting languages are you proficient in, and how have you used them?

Mention specific scripting languages you are comfortable with, such as Python or Bash. Provide examples of tasks you automated with scripting, illustrating how these scripts improved efficiency and consistency in your processes.

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Can you describe your experience with ML frameworks such as TensorFlow or PyTorch?

Share details about projects you've completed using ML frameworks, focusing on your role and contributions. Discuss specific functionalities of the frameworks you utilized and any challenges you overcame while integrating them into your workflows.

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What tools do you use for monitoring and log analysis?

Enumerate the monitoring and log analysis tools you're familiar with, such as ELK, Grafana, or Prometheus. Discuss how you've set up monitoring solutions to ensure system health and how you’ve utilized logs for troubleshooting and performance tuning.

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Describe a challenging problem you faced as a DevOps MLOps Engineer and how you solved it.

Use the STAR method (Situation, Task, Action, Result) to outline a specific challenge, your role in addressing it, the actions you took, and the successful outcome. This shows how you think critically and approach problem-solving.

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In your opinion, what makes a successful DevOps MLOps Engineer?

Your answer can reflect on crucial skills such as adaptability, continuous learning, and communication. Emphasize the importance of collaboration with teams and staying updated with the latest technology trends to drive success in this role.

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How do you document system architecture and processes?

Discuss your methodology for documenting architectures and procedures, including which tools or software you find most effective. Highlight why documentation is key in streamlining operations and facilitating audits.

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What do you enjoy most about working as a DevOps MLOps Engineer?

Share what aspects of the job excite you, whether it's solving complex engineering problems, collaborating with talented teams, or working with cutting-edge technology developments. This helps to convey your passion and commitment to the role.

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Full-time, hybrid
DATE POSTED
December 27, 2024

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