remote
MLOps Developer - L'Oreal
Software Engineer
Join a cutting‑edge AI team as an MLOps Developer, building and scaling production‑grade computer‑vision pipelines for AR beauty applications using Python, TensorFlow, Docker, Kubernetes and cloud services.
About the role
Key Responsibilities
- Design, implement, and maintain end‑to‑end MLOps pipelines for real‑time facial‑recognition and AR models.
- Containerize machine‑learning services with Docker and orchestrate deployments on Kubernetes clusters.
- Automate model training, validation, and continuous integration/continuous deployment (CI/CD) workflows using tools such as GitHub Actions or Jenkins.
- Monitor model performance in production, set up alerting, and iterate on model improvements.
- Collaborate with data scientists, software engineers, and product teams to translate research prototypes into scalable, reliable services.
Requirements
- Strong proficiency in Python and experience with deep‑learning frameworks (TensorFlow or PyTorch).
- Hands‑on experience with Docker, Kubernetes, and cloud platforms (AWS preferred).
- Solid understanding of CI/CD principles and tooling for ML lifecycle management.
- Familiarity with model serving, monitoring, and versioning (e.g., MLflow, Seldon).
- Excellent problem‑solving skills and ability to work in a fast‑paced, interdisciplinary environment.
Skills
pythontensorflowdockerkubernetesawscicd