MLOps Engineer (m/f/d). A competency profile.
The competency profile validates your domain expertise in data. It recognizes you as a Senior practitioner and advances your career to Senior and Lead. By practitioners, for practitioners - this service is provided by AI Guild members recognized for their expertise.
Here is the example of an MLOps engineer
Maimuna Lubega worked as an ML engineer for two years after completing an M.Sc. in Data Science (UK). Previously she worked as a software engineer for two years (US). Her experience ranges from building ML infrastructure and writing data processing pipelines to model prototyping and productionization. Her dual qualification in computer science and data science supports her focus on MLOps.
What do you see in the competency profile?
You are looking at the profile of someone able to productionize models (MLOps) while also advancing the company's data infrastructure (data engineering).
MLOps: Maintaining training and deployment systems to minimize failure while providing CI/CD.
Data Engineering: Delivering and improving a quality data infrastructure.
She has been developing her expertise by deploying NLP and Computer Vision models, including contributions to model development.
MLOps and the relevance of data engineering
The profile shows how her model training and deployment is embedded in a focus on productionization, e.g., testing, CI/CD, microservices.
It highlights her MLOps expertise, especially her commitment to data quality to ensure the reproducibility of models.
Her background in computer science adds another layer: Understanding the importance of writing clean code and delivering it.
Where is her #datacareer headed?
You are looking at a must-have Senior MLOps profile combining all the essential elements required of an expert: The ability to productionize with a keen eye for the quality of data and code and the implementation of a rigorous test regime.
To take the next step, she most likely will be prioritizing NLP or Computer Vision. Language and image are not the same types of data. So, becoming a recognized domain expert is easier if you focus on one type of data.
How to get your competency profile?
Are you in Year 2, 3, or 4 of your #datacareer? Would you like to find out how you efficiently show and develop your expertise? It takes 60 days to complete the competency profile. To start, point us to your LinkedIn or GitHub profile (or similar) here.