Software Engineer II- MLOps | Remote

Role Summary:

We are seeking an experienced and talented Engineer to join our MLOps team. In this role, you will play a crucial part in designing, developing, and maintaining scalable and reliable machine learning operations (MLOps) pipelines and infrastructure. You will collaborate closely with data scientists, software engineers, and other stakeholders to ensure the successful deployment and monitoring of machine learning models in production environments.

Responsibilities:

• Design and implement robust MLOps pipelines for model training, evaluation, deployment, and monitoring using industry-standard tools and frameworks
• Collaborate with data scientists to streamline the model development process and ensure seamless integration with MLOps pipelines.
• Optimize and scale machine learning infrastructure to support high-performance model training and inference.
• Contribute to the development of MLOps standards, processes, and documentation within the organization.
• Mentor and support junior team members in MLOps practices and technologies.
• Stay up-to-date with the latest trends and best practices in MLOps, and explore opportunities for continuous improvement.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Statistics, or a related field.
• 2+ years of experience in software engineering, with  some experience in ML
• Proficient in Python and at least one other programming language (e.g., Java, Go, C++).
• Good experience with containerization technologies (Docker, Kubernetes) and cloud platforms (AWS, GCP, Azure).
• Familiarity with machine learning frameworks and MLOps tools
• Experience with big data technologies
• Strong understanding of CI/CD principles and practices.

Preferred Qualifications:

• Familiarity with model serving frameworks
• Knowledge of infrastructure as code (IaC) tools
• Experience with monitoring and observability tools
• Contributions to open-source MLOps projects or communities.