Senior ML ops Engineer

ABOUT US

Voyage81 is the computer vision branch of ODDITY, a consumer-tech platform built to transform the global beauty, wellness, and health markets. Integrating advanced technologies, machine learning computer vision models, and data science allows us to invent ourselves with unique new brands and develop exceptional products delivering a superior consumer experience. ODDITY’s top brands, IL MAKIAGE, and SpoiledChild have already brought millions of consumers to shop for beauty and wellness products online for the first time.

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