TL;DR

Senior Machine Learning Engineer (Data Science): Developing and deploying machine learning models that drive impactful decisions and elevate customer experiences across the full value chain, from jewellery design to retail and marketing, with an accent on end-to-end analytical product development and data pipeline engineering. Focus on optimizing retail operations, ensuring model scalability, reliability, and continuous performance monitoring in production environments.

Location: Hybrid Work in Istanbul, Turkey

Company

%hirify_global% is hiring for a global jewelry company.

What you will do

Work on end-to-end analytical products, from exploration to productization and testing.
Develop and maintain data pipelines to collect, process, and analyze large datasets.
Deploy machine learning models into production environments, ensuring scalability and reliability.
Collaborate with cross-functional teams to translate business needs into machine learning solutions.
Continuously monitor the performance of deployed models and implement improvements.
Stay up-to-date with the latest developments in machine learning and AI, applying new techniques.

Requirements

Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Applied Mathematics, or a related field.
4-7 years of experience as a Machine Learning Engineer, Data Scientist, or similar role.
Strong proficiency in Python.
Ability to work with machine learning tools (e.g., scikit-learn, TensorFlow, Keras, PyTorch, Spark MLlib).
Experience with big data using Databricks, Snowflake, Apache Spark, or Hadoop.
Proficiency in SQL and experience with relational databases.
System-level architecture understanding, including scaling, MLOps, and model/data monitoring.

Nice to have

Experience in the retail industry or e-commerce.

Culture & Benefits

Paid Vacation, Sick Days, and Holidays Day Off.
Hybrid Work (home/office).
Sport/Insurance Compensation, Training Compensation, and Transportation compensation.
English Classes.
Supportive environment encouraging creative problem-solving and continuous learning.

ML Engineer (Data Science)