Vincent Claes, AWS Machine Learning Engineer

Description

- Building production-ready data pipelines in the machine learning field;

- Let data scientists focus on data exploration, feature engineering and modeling;

- Advocating end-to-end ownership and a product mindset;

- Focus on cloud and serverless services.

Websites

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- Github: - Medium: - StackOverflow: - Linkedin:

Languages

Dutch
Native or bilingual

Workplace preferences

Remote only

Primarily works remotely

KBC
ML (Ops) Engineer
BANKING AND INSURANCE
September 2021 - Today (4 years and 9 months)
Leuven, Belgium
Setup and maintain the tools data scientists use.
Deploy Models for batch as for real-time inference.
Challenge and evolve the MLOps architecture.

Technology toolbelt: Python, AWS Serverless services, AWS Sagemaker, AWS EKS, Jupyter, MLFlow, Terraform, Concourse (CICD).
Python AWS Sagemaker Terraform CICD
AXA
Data / ML Engineer
BANKING AND INSURANCE
March 2018 - September 2021 (3 years and 7 months)
Brussel, Belgium
Build production ready ML pipelines in the field of Natural Language Processing (NLP);
Develop and implement ML Ops best practices;
Build applications that serve machine learning models;
Focus on serverless cloud services;

Technology toolbelt: Python, Pyspark, Git/Github, Serverless framework, AWS CDK
AWS experience: Glue, Sagemaker, Stepfunctions, Codebuild, Lambda, API Gateway, S3, Athena, Cloudwatch, SNS, SQS, Kinesis Firehose.
Python Apache Spark MLlib Spark AWS CICD ML MLOps

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Signup to reveal

AWS Certified Machine Learning – Specialty
AWS
2021
https://www.credly.com/badges/e7ac83b4-1383-4ed4-987a-6e35071e32e1?source=linked_in_profile
AWS Certified Developer – Associate
AWS
2020
https://www.credly.com/badges/94d105e1-2108-4e6c-b85b-6e53488a4c4f?source=linked_in_profile

Business Engineering
KUL
2011