ML Platform Engineer | Hybrid & Cloud

We believe that technology is the driver and e-commerce is the outcome. Thanks to the dedication of our team, we have become one of the top 5 e-commerce companies in EMEA and one of the fastest growing worldwide. We currently deliver over 1.5 million parcels daily to 27 countries.

Growth is in our DNA

As a young and dynamic company, we are constantly growing and expanding. With Trendyol Tech, one of the leading R&D centres, Trendyol Express, the fastest growing delivery network, Dolap, the largest platform for second-hand goods, and Trendyol Go, our instant food and grocery delivery service, we are gearing up to become the world's leading e-commerce platform.

Focused on positive impact

Our vision goes beyond business success. We strive to make a sustainable and positive impact on our customers, business partners, and society. By digitizing merchants and SMEs, helping businesses grow, and promoting women's economic empowerment, we are dedicated to creating a better future.

ABOUT THE TEAM

If you are a techie, you belong in our Technology Team that builds scalable, high-performance platforms for our customers using up-to-date and efficient technologies.

We are all working with the same purpose:
To create a positive impact in our ecosystem by enabling commerce through technology.

Your Main Responsibilities

• Working on large-scale machine learning and data challenges that impact millions of people every day
• Building and maintaining a data infrastructure, services, and pipelines that make data more accessible to the teams
• Maintaining, scaling, and improving our clusters to support the data-science team
• Participate in code and design reviews for our machine learning applications to maintain our high coding standards
• This position will play a crucial role in the full product development lifecycle.
• Build and configure multi-tenant machine learning environments on-prem, cloud, or hybrid
• Interact with teams of engineers from multiple domains
• Create, schedule, version, iterate, and monitor data science pipelines
• Design, deploy, and monitoring tools such as feature stores, and feature/model drift detectors to support the data science ecosystem
• Maintain the correct operation of the system, looking for improvements in availability and monitoring
• Build a solid engineering foundation within the Data Science team
• Developing tools to enable the Data Science teams

Qualities We Are Looking For

• Bachelor's or master's degree in computer science, natural sciences, mathematics, or equivalent qualification
• 3+ years of experience handling machine learning and data-pipelines operations
• Experience with running Machine Learning Systems in Production
• Experience with ml-ops tools, data engineering, and dev-ops
• Experience with at least one CI/CD tool and/or infrastructure as a code tool, e.g. Terraform, Ansible, Jenkins, Github actions, or cloud platforms
• Experience in cloud infrastructure, e.g. GCP, AWS, etc.
• Experience in application containerization and orchestration tools - Docker, Kubernetes, or cloud equivalents
• Experience with Pipeline Tools, e.g. Kubeflow, Airflow, or cloud equivalents
• Excellent coding skills with the attitude of clean, reusable, and well-documented code, reproducibility, and testing
• A willingness to dive deep, experiment rapidly, and get things done
• Nice to have:
• Solid relational DB skills and SQL experience
• Experience with in the Python ecosystem (Pandas, numpy, Jupyter, etc.)

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JOIN US AND

• Take responsibility from day one and develop your skills with a talented and diverse international team.
• Experience open communication, flexibility, and a start-up spirit in our unique culture.
• Tackle big challenges in e-commerce with Agile practices and encourage growth by…