Our team is seeking an experienced Machine Learning Engineer to join us in optimizing the deployment and management of machine learning models in the fast-paced e-commerce and logistics industry.

We are a dynamic, growing organization that values innovation, technical excellence and using leading edge tools.

If you are passionate about data science and excited to work on large scale projects that directly impact the growth of e-commerce and streamlining of logistics processes, this is the perfect opportunity for you.

Responsibilities:Develop and implement machine learning model deployment strategies, including infrastructure management and automation.Oversee the entire lifecycle of ML models, from experimentation and training to deployment and monitoring, considering industry-specific needs.Establish and maintain coding and deployment standards for data science projects.Create scalable tooling and infrastructure used across Data & AI team.Collaborate closely with data science, data engineering and data consulting teams.What we need from you:At least three years of experience in the role of ML Engineer/MLOps/Data Scientist /Python Developer.Proficiency in Python 3, as well as ML and data processing libraries.Following software engineering best practices.Knowledge of ML models life cycle and management (mlflow).Experience in leveraging CI/CD pipelines in data-based products.Experience with data pipelines framework, preferably Kedro.Experience with CLI tools: bash/zsh.Experience in writing tests.Experience with big data processing (Spark)Experience with the following is nice to have:DatabricksDocker and kubernetesSchedulers like Airflow/Prefect.LLMs and RAGs.Fastapi/Django/Flask.