Akkodis, is a global leader in the engineering and R&D market that is leveraging the power of connected data to accelerate innovation and digital transformation.
With a shared passion for technology and talent, 50,000 engineers and digital experts deliver deep cross-sector expertise in 30 countries across North America, EMEA and APAC.
Akkodis offers broad industry experience, and strong know-how in key technology sectors such as mobility, software & technology services, robotics, testing, simulations, data security, AI & data analytics.
The combined IT and engineering expertise brings a unique end-to-end solution offering, with four service lines – Consulting, Solutions, Talents and Academy – to support clients in rethinking their product development and business processes, improve productivity, minimize time to market and shape a smarter and more sustainable tomorrow.
Akkodis is part of the Adecco Group.
Akkodis is a commercial brand under which both AKKA and Modis entities operate.
Job Opportunity: Machine Learning Operations Engineer Are you passionate about the intersection of machine learning and software development?
Do you have experience in setting up and configuring ML environments and deployment tools?
Our client, a dynamic and innovative organisation, is seeking a talented Machine Learning Operations Engineer to join their team.
If you thrive in a collaborative and fast-paced environment and are excited about driving best practises in ML model development and deployment, this could be the perfect opportunity for you!
What you'll be doing Working with cutting-edge technologies like Kubernetes and Docker to set up and configure ML environments.
Writing scripts to automate workflows and ensure reproducibility of ML experiments.
Conducting regular performance reviews and data audits of deployed models.
Troubleshooting issues related to model performance and infrastructure.
Participating in cross-functional teams to drive best practises in ML model development and deployment.
Collaborating with development teams to enable the delivery of high-quality, secure, and scalable applications on the cloud with automated tools and scripts.
Identifying solution opportunities that focus on reusing code and maximising the return on development costs.
Recommending best practises to ensure robust, secure, and scalable products are developed.
Participating in agile threat modelling and vulnerability management.
Ensuring compliance with security and regulatory requirements.
Developing solutions where data can bring value to our offers and customer experience.
Supporting the Customer Enterprise/Solution Data Architects in coordinating data landscaping and cataloguing.
What you bring to the table Solid experience in setting up and configuring ML environments and deployment tools.
Proficiency in scripting to automate workflows and ensure reproducibility of ML experiments.
Strong troubleshooting skills to address issues related to model performance and infrastructure.
Knowledge of CI/CD pipelines to enable efficient deployment of code and automating development and deployment processes.
Excellent collaboration skills to work effectively with cross-functional teams.
A passion for driving best practises in ML model development and deployment.
Experience in developing high-quality, secure, and scalable applications on the cloud.
Familiarity with agile threat modelling and vulnerability management.