A Machine Learning Engineer is a cloud and software engineer with some basic knowledge in data modelling.
A ML Engineer is an advanced developer in a least one of the following languages: Java, Python, C, C++.
Key duties and 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, …
Best-practices: CML and deployment
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
Required experience & competencies
~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 cloudRespect 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 technologiesSQL basic knowledgeIntermediate level and understanding in Operating SystemsUsage of shellSeek 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 workProactively supports other team members with technical help and adopts a team mindsetIs realistic with timeframes and updates relevant stakeholders on progressCan rigorously document a project in plain EnglishBusiness acumen
Proactively identifies and raises technical concerns/doubts on data projects Understands instructions and contributes to the vision by questioning or enriching the tasks defined during a projectRequired Education
Master’s degree (Ph. D.
is a plus) in Software engineering, Technology, Engineering, , Computer Science or similar quantitative fieldBachelor’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.)