N-iX is looking for a passionate and motivated Data ML Engineer to join our team.
Our customer is a technology company that powers one of the world’s largest two-sided marketplaces for high-quality photos, illustrations, videos and music used by individuals, businesses, marketing agencies and media organizations of all sizes. In this role, you will be working with highly motivated and talented data scientists and engineers who are primarily focused on developing next generation AI/ML systems that transform the way people find content they enjoy.

Responsibilities:

• Partner with product managers, data scientists and other technical stakeholders to understand requirements and collaborate on providing solutions at scale.
• Create end-to-end machine learning solutions from start to finish, contribute tocomplex machine learning operations and inference pipelines.
• Build and maintain a modern serverless ML-powered GraphQL stack that willsupport rapid iteration and drive delivery of AI-powered features.
• Support development, productionalization and deployment of machine learningmodels.
• Manipulate large datasets quickly and efficiently in both relational and “big” data stores.
• Day-to-day operational support of engineering infrastructure, products, andservices, including on-call routine.

Requirements:

• Industry experience in building, deploying and maintaining high performing,resilient, and scalable real-time machine learning systems.
• Expert knowledge of Python and experience in building micro-services that canscale effectively.
• Knowledge of SQL, data modelling, and dimensionality modelling concepts
• Familiarity with modern ETL stack (Airflow, DBT, Snowflake) and streamprocessing frameworks (Kafka, Kinesis).
• Good understanding of machine learning operation practices and procedures.
• Familiarity with machine learning principles, hands-on experience with common machine learning tools like Scikit-Learn and deep learning frameworks like TensorFlow, Keras, Torch/PyTorch
• Experience with Cloud infrastructure provisioning and integration patterns
• Be excited to be part of the team, have the ability to communicate clearly anddevelop close working relations with other team members and stakeholders.
• Ability to innovate and identify new approaches to improve current practices.

• Partner with product managers, data scientists and other technical stakeholders to understand requirements and collaborate on providing solutions at scale.
• Create end-to-end machine learning solutions from start to finish, contribute tocomplex machine learning operations and inference pipelines.
• Build and maintain a modern serverless ML-powered GraphQL stack that willsupport rapid iteration and drive delivery of AI-powered features.
• Support development, productionalization and deployment of machine learningmodels.
• Manipulate large datasets quickly and efficiently in both relational and “big” data stores.
• Day-to-day operational support of engineering infrastructure, products, andservices, including on-call routine