Job Description:
We are looking for a motivated Junior MLOps Engineer to join our MLOps & Data Engineering team. In this entry-level role, you will support the deployment, monitoring, and maintenance of machine learning models in production environments. You will work closely with senior engineers and data scientists to build scalable and reliable ML pipelines, ensuring smooth model lifecycle management.
Key Responsibilities:
- Assist in building and maintaining automated ML pipelines for training, deployment, and monitoring.
- Support the integration of machine learning models into production systems.
- Monitor model performance, detect issues, and collaborate on troubleshooting.
- Help manage infrastructure for ML workflows using cloud platforms and container orchestration tools.
- Work with data engineering teams to ensure data quality and availability for ML pipelines.
- Participate in code reviews, testing, and documentation of MLOps processes.
- Learn and apply best practices in model versioning, reproducibility, and CI/CD for ML.
- Stay up to date with emerging MLOps tools and technologies.
Requirements:
- Bachelor’s degree in Computer Science, Engineering, Data Science, or related field, or equivalent practical experience.
- Basic understanding of machine learning concepts and software engineering principles.
- Familiarity with programming languages such as Python or Bash.
- Exposure to cloud platforms (AWS, Azure, GCP) and container technologies like Docker and Kubernetes is a plus.
- Knowledge of CI/CD pipelines and version control systems (e.g., Git).
- Strong problem-solving skills and eagerness to learn.
- Good communication and teamwork abilities.
