THE OPPORTUNITY
We are looking for a highly skilled and independent ML Ops Engineer to drive the deployment, optimization, and scaling of our computer vision deep learning models. This role is ideal for someone who thrives in a fast-paced, high-impact environment, takes ownership, and demonstrates strong leadership skills while collaborating across teams. This is an opportunity to have a real impact in a fast-growing company backed by the big-scale data of ODDITY’s growing brands.
KEY RESPONSIBILITIES
- Collaborate with machine learning engineers and data managers to improve, validate, and deploy ML models at a large scale.
- Design and implement large-scale data pipelines using cloud computing.
- Design, and implement, and deploy large-scale pipelines for ML models in production
- Maintenance and monitoring of performance reliability, and scalability.
- Work with us to continually grow and improve our ML workflows, tools, and data, to enhance our ML and data tools and workflows.
YOU SHOULD BRING WITH YOU
- 3+ years of software development experience in Python
- Strong experience with AWS Cloud services (Lambda, S3, ECS, EKS, EC2, etc.)
- Expertise in Kubernetes & Docker for containerized ML model deployments.
- Experience in orchestrating Machine Learning solutions for large-scale production.
- Deep understanding of CI/CD pipelines for ML models (GitHub Actions, etc.).
- Experience in Machine Learning Orchestration ( data version control, ML flow).
- Experience with ML Model Monitoring (e.g., Seldon, Grafana).
- Knowledge of Data Engineering Tools ( Airflow, Spark, or similar).
- Independence & Proactiveness – A self-starter approach who pushes boundaries and drives projects to completion.
- Strong Communication & Leadership Skills – Ability to work across teams and drive ML Ops best practices.
Nice-to-Have Skills
- Experience with MLOps frameworks (clearML / SageMaker / W&B) – Advantage
- Experience with TensorFlow – Advantage
- Familiarity with GPU-based model deployment and optimization – Advantage
- Background in computer vision and deep learning workflows – Advantage
- B.Sc in Computer Science or equivalent – Advantage






















