Velocity Tech has partnered with a heavily funded tech startup who are looking for a MLOps Engineer to join their team on a permanent basis.
This opportunity is unable to sponsor visas at the moment.
Key Responsibilities:
- Design, build, and maintain scalable infrastructure for deploying machine learning models.
- Implement and manage MLFlow for tracking experiments, model management, and reproducibility.
- Use Terraform to automate and manage cloud infrastructure (AWS, GCP, or Azure).
- Collaborate with data scientists and software engineers to automate workflows, data pipelines, and CI/CD for machine learning projects.
- Ensure the reliability and availability of machine learning services in production.
- Monitor and optimize the performance of models and infrastructure in a cloud environment.
- Stay updated with the latest trends and technologies in MLOps, cloud infrastructure, and machine learning.
Requirements:
- Proven experience in MLOps or DevOps roles focused on machine learning workflows.
- Strong experience with MLFlow for managing experiments and model lifecycle.
- Proficiency with Terraform for infrastructure-as-code in cloud environments.
- Expertise in cloud platforms such as AWS, GCP, or Azure.
- Experience with containerization (Docker, Kubernetes) and orchestration tools.
- Strong understanding of CI/CD pipelines and automation for ML.
- Proficiency in Python and common ML libraries (TensorFlow, PyTorch, Scikit-learn).
- Excellent problem-solving skills and the ability to work in a fast-paced environment.