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Machine Learning Ops Engineer

Remote: 
Full Remote
Contract: 
Experience: 
Mid-level (2-5 years)
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Offer summary

Qualifications:

Work experience in machine learning projects, Familiarity with Apache Airflow, sklearn, MLFlow, TensorFlow, Knowledge of MLOps architecture and practices, Proficient in SQL for data manipulation, Experience in cloud environments like GCP.

Key responsabilities:

  • Manage the lifecycle of machine learning models
  • Support development, training, and deployment of ML models
  • Ensure effective monitoring and maintenance
  • Work with automation and performance optimization tools
  • Utilize CI/CD pipelines for deployment
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Job description

An MLOps Engineer is responsible for managing the lifecycle of machine learning models, ensuring they are deployed, monitored, and maintained effectively. The MLOps Engineer supports the development, training, and deployment of machine learning models, and key skills involve CI/CD Pipelines, Model Deployment, Monitoring and Maintenance, Automation and Performance Optimization.

Skills requirement

Must Have:

  • Relevant work experience in ML projects
  • Relevant work experience in technologies and frameworks used in ML, examples are: Apache Airflow, sklearn, MLFlow, TensorFlow
  • Knowledge of MLOps architecture and practices
  • Knowledge of data manipulation and transformation, e.g. SQL
  • Experience working in cloud environment (e.g. GCP) 
  • Programming in Python
  • Experience with monitoring and observability (ELK stack)
  • Familiar with software engineering practices like versioning, testing, documentation, code review
  • Deployment and provisioning automation tools e.g. Docker, Kubernetes, Openshift, CI/CD

Nice to Have: 

  • Experience with distributed systems and clusters for both batch as well as streaming data (S3/Spark/Kafka/Flink) 
  • Affinity with Advanced Analytics, Data Science, NLP
  • Hands-on experience building complex data pipelines e.g. ETL 
  • System design and architecture 
  • Bash scripting and Linux systems administration 
  • Programming in a statically typed language, e.g. Scala, Java 
  • Experience with building distributed, large scale and secure applications 
  • Experience with working in an agile/scrum way 
  • Being a committer to Open-Source projects is a strong plus 

Required profile

Experience

Level of experience: Mid-level (2-5 years)
Spoken language(s):
English
Check out the description to know which languages are mandatory.

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