MLOps Engineer

Job Summary:

We are looking for an experienced MLOps Engineer to join our team. The ideal candidate will have a strong background in machine learning, software engineering, and DevOps practices. You will be responsible for developing and maintaining our machine learning infrastructure, ensuring smooth deployment and operation of machine learning models in production.

Key Responsibilities:

• Design, build, and maintain scalable machine learning infrastructure.
• Develop and implement CI/CD pipelines for machine learning models.
• Collaborate with data scientists and software engineers to deploy and monitor machine learning models in production.
• Ensure the reliability, performance, and scalability of machine learning systems.
• Implement monitoring and logging solutions to track model performance and data quality.
• Automate the process of model training, evaluation, and deployment.
• Manage and maintain cloud resources for machine learning workloads.
• Stay up-to-date with the latest developments in MLOps tools and technologies.

Required Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• 2+ years of experience in MLOps, DevOps, or a related field.
• Strong programming skills in Python and experience with machine learning libraries (e.g., TensorFlow, PyTorch).
• Proficiency with CI/CD tools (e.g., Jenkins, GitLab CI).
• Experience with cloud platforms (e.g., AWS, GCP, Azure).
• Familiarity with containerization technologies (e.g., Docker, Kubernetes).
• Strong problem-solving skills and attention to detail.
• Excellent communication and collaboration skills.

Preferred Qualifications:

• Experience with infrastructure-as-code tools (e.g., Terraform, CloudFormation).
• Knowledge of data engineering and data pipeline tools (e.g., Apache Airflow, Apache Kafka).
• Understanding of security best practices in machine learning deployments.
• Experience with monitoring and logging tools (e.g., Prometheus, Grafana).