MLOps Engineer

MLOps Engineer Job Description

About the Role

We are seeking an experienced MLOps Engineer to design and implement robust MLOps solutions that seamlessly integrate with our existing CI/CD pipelines and data platforms. You will develop automated tools and frameworks for model training, testing, deployment, and monitoring, ensuring efficient and scalable machine learning operations.

Key Responsibilities

- Design & Implementation: Create and implement robust MLOps solutions that integrate with existing CI/CD pipelines and data platforms.

- Automation: Develop automated tools and frameworks for model training, testing, deployment, and monitoring.

- Collaboration: Work closely with data scientists and software engineers to ensure operational and architectural alignment.

- Infrastructure Maintenance: Maintain and optimize machine learning infrastructure for performance and scalability.

- Best Practices: Implement best practices for data governance, security, and compliance in machine learning operations.

- Continuous Improvement: Continuously research and integrate new MLOps tools and methodologies to enhance workflow efficiencies.

About You

You might be a strong candidate if you have:

- Educational Background: Bachelor's Degree in Computer Science or a similar quantitative field. A Master's degree or PhD is preferred.

- Experience:

- 4+ years of experience in Machine Learning and related fields.

- 2+ years of experience in an MLOps or related role, with a proven track record of deploying and managing ML systems in production.

- Technical Skills:

- Strong knowledge of machine learning frameworks (e.g., TensorFlow, PyTorch) and programming languages (e.g., Python, Scala).

- Experience with containerization technologies (e.g., Docker, Kubernetes) and cloud services (e.g., AWS, Azure, Google Cloud).

- Familiarity with data orchestration tools (e.g., Apache Airflow) and model monitoring solutions.

- Soft Skills: Excellent problem-solving, teamwork, and communication skills.

- Certifications: Certifications in relevant technologies (e.g., AWS Machine Learning, Kubernetes) are a plus.