A global leader in engineering and R&D, Akkodis accelerates innovation and digital transformation with connected data. With 50,000 engineers and experts in 30 countries, Akkodis offers deep cross-sector expertise in mobility, software, robotics, and data security. The company provides a unique end-to-end solution offering with four service lines: Consulting, Solutions, Talents, and Academy. Akkodis is part of the Adecco Group.
Akkodis is a commercial brand under which AKKA and Modis entities operate.
A dynamic organisation seeks a Machine Learning Operations Engineer to join their team. The ideal candidate is passionate about the intersection of machine learning and software development, with experience in setting up and configuring ML environments and deployment tools.
The successful candidate will work with cutting-edge technologies like Kubernetes and Docker, write scripts to automate workflows, and conduct regular performance reviews of deployed models. They will troubleshoot issues related to model performance and infrastructure, participate in cross-functional teams, and collaborate with development teams to deliver high-quality applications on the cloud.
The ideal candidate has solid experience in setting up and configuring ML environments, proficiency in scripting, strong troubleshooting skills, and knowledge of CI/CD pipelines. They must have excellent collaboration skills, a passion for driving best practises in ML model development and deployment, and experience in developing high-quality, secure, and scalable applications on the cloud.
* Set up and configure ML environments using Kubernetes and Docker.
* Write scripts to automate workflows and ensure reproducibility of ML experiments.
* Conduct regular performance reviews and data audits of deployed models.
* Troubleshoot issues related to model performance and infrastructure.
* Participate in cross-functional teams to drive best practises in ML model development and deployment.
* Collaborate with development teams to enable the delivery of high-quality, secure, and scalable applications on the cloud.
* Identify solution opportunities that focus on reusing code and maximising the return on development costs.
* Recommend best practises to ensure robust, secure, and scalable products are developed.
* Participate in agile threat modelling and vulnerability management.
* Ensure compliance with security and regulatory requirements.
* Develop solutions where data can bring value to our offers and customer experience.
* Support the Customer Enterprise/Solution Data Architects in coordinating data landscaping and cataloguing.