Machine Learning Engineer

Overview

Job Title: ML Engineer

Mission:

Machine Learning Engineers promote the adoption of best standards in industrial code development across the ML&AI community. They do so by developing ML pipelines that are production-ready by design or by integrating existing ML solutions into industrial pipelines.

They participate in the development, deployment and monitoring of AI services, which means they contribute to data quality checks, data flow design, the design of the models themselves and their overall integration into the production environment.

ML Engineers are meant to facilitate the communication between AI & Analytics teams and IT production with regards to the deployment of ML models, ensuring that models put in production are equipped with the appropriate data pipelines and monitoring.

Principal assignments:

ML Engineers contribute to Machine Learning projects by:
• Working with the Data Scientists to define and develop the target solution with production constraints in mind. This allows to select the correct run infrastructure and serving model (e.g. data ingestion scheme, API synchronicity, …) to address the business requirements (real-time responses, processing volumetry, …)
• Contributing to the automation of the different elements of the ML pipeline in order to integrate and deploy them in the production environment (e.g. building Docker/VM images, prepare unitary, regression and integration tests, …)
• Supporting Data Scientists on the usage of the existing industrial solutions available to build and monitor AI services (i.e. the CI/CD tools)
• Supporting IT Production on the parameterization of the target environment
• Ensuring that the model runs without errors, is retrained if needed (incl. automatically) and is monitored both from the IT and the business perspective.

Experience in the relevant domain:

Techniques:
• Containerization / virtualisation
• AI platforms & IDEs
• CI/CD
• Code, model & data versioning
• IT language of their entity or project
• ML packages and libraries relevant to their entity or project
• Model compression techniques
• ELT / ETL tools
• Big data tools
• Data flow processing
• Cloud computing services
• Relational databases and NoSQL
• Data visualization tools

Attitude:

Behavioral skills:
• Communication skills – oral & written
• Ability to deliver/Results driven
• Attention to detail/rigor
• Creativity & Innovation/Problem Solving
• Proactively invests time in continuous learning and knowledge improvement.
• Demonstrates awareness of efficiency and efficacy.
• Thinks out of the box outside existing processes and frameworks.
• Works with energy and empowerment to deliver great results and a large contribution to the company’s success
• Is constructive by being open to the changes and to other’s opinions, ideas and feedback

Company:

Cognizant

Qualifications:

Language requirements:

Specific requirements:

Educational level:

Level of experience (years):

Senior (5+ years of experience)

Tagged as: Belgium, Big Data, Data Visualization, Industry, Machine Learning, NLP