ML Ops Engineer

We are seeking an experienced ML Ops Engineer to join an innovative consumer-tech platform revolutionizing the global beauty, wellness, and health markets. The platform leverages advanced technologies, including data science, machine learning models, and computer vision, to create exceptional products and deliver a superior consumer experience. Our top brands have already brought millions of consumers worldwide to shop for beauty and wellness products online for the first time.

This is an exciting opportunity 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 our 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 us to constantly grow and improve our ML workflows, tools, and data with us, to keep improving our ML and data tools and workflows.

Requirements:

• 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.

• At least Upper-Intermediate English.

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.

• Master's Degree. in Computer Science or equivalent - Advantage.

We offer:

• Long-term employment with competitive compensation, based on experience.

• Possibility to work remotely.

• An open, transparent, and fun work culture.

• Multi-national team and collaborative work environment.

• Continuous knowledge sharing with engaged co-workers.

• Career and professional growth opportunities.