Responsibilities

ML Engineers are accountable for:
•    The industrialization of models
•    Performant and scalable architecture
•    Optimization of model fine tuning
•    Deployments on self-managed infrastructure (e.g., self-managed cloud env)
•    Facilitation of Deployments on SCOR IT infrastructure 
•    The creation and maintenance of the ML Ops framework
•    Quality: reproducibility, experiment tracking, …
•    Availability: model storage, …
o    Best-practices: CML and deployment
o    Monitoring: drift, logs, performance
•    Coordination with different infrastructure owners or Solutions Owner to ensure application deployment (following DAS/IT framework).

Compliance
•    Adhere to all Information Security policies and best practices, including security awareness training and other information protection initiatives
•    Be fully compliant with GDPR and other local data protection legislation 
•    Be aware of regulatory and reputational risk when developing consumer-facing AI tools and suggest ways of mitigating these
 

Qualifications

• Master’s degree (Ph. D. is a plus) in Software engineering, Technology, Engineering, , Computer Science or similar quantitative field
• Bachelor’s degree or similar work experience is accepted in place of a relevant Master’s degree.
• Certifications in open-source components are a plus (CKAD, Docker etc.)
• ~1-3 years’ experience in software programming capabilities and knowledge running models into production (containers, API)
• Be an efficient software engineer with a good command of at least one of the following languages: Python, Java, Golang or C++
• Be able to industrialize machine learning or deep learning models in the cloud
• Respect the SCOR DAS IT framework (development framework): unit test, linting, typing, …
• Read technical documentation/blogs on latest features of a programming language and cloud features
• Knowledge and familiarity with code versioning tools
• Basic knowledge of containerization technologies
• SQL basic knowledge
• Intermediate level and understanding in Operating Systems
• Usage of shell
• Seek for answers by themselves by knowing the key concepts to look at (debugging code, google right terms, looking for proper help)
• Fluent with git (gitflow) and capable to implement CI/CD

Communication skills

• Shares and communicates about his/her work to the rest of the technical team with accurate terms 
• Documents his/her work (be able to write a technical report with explicit relevant and self-explicit charts, follow templates, etc.)
• High level controls on his/her work
• Proactively supports other team members with technical help and adopts a team mindset
• Is realistic with timeframes and updates relevant stakeholders on progress
• Can rigorously document a project in plain English