This opportunity is for the computer vision division of our client,- a direct-to-consumer consumer-tech platform built to transform the global beauty, wellness, and health markets. Integrating advanced technologies, including data science, machine learning models, and computer vision, allows us to develop industry-innovating ourselves with unique new brands and develop exceptional products that deliver a superior consumer experience. Our client’s top brands have already brought millions of consumers worldwide to shop for beauty and wellness products
online for the first time.

We are looking for a highly skilled and independent ML Ops Engineer to drive the deployment, optimization, and scaling of the 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 our client’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 and reliability, and scalability.
- Work with our client to constantly grow and improve the ML workflows, tools, and data.

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.
- B2+ English proficiency (our client's primary communication language)
- 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
- MB.Sc. in Computer Science or equivalent - Advantage

Benefits and working conditions:
- Competitive salaries
- 20 working days paid vacation, including paid compensation if the vacation days weren’t used
- Health insurance including dentist
- Gym membership
- Training programs and coaching to support career development and more
- Corporate celebrations, team-building events, fun activities, and more