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MLOps Engineer

Eqvilent

Roles & Responsibilities

  • Strong knowledge of Python
  • Familiarity with Docker
  • Basic understanding of machine learning concepts and techniques
  • Experience with PyTorch and Kubernetes is a plus.

Requirements:

  • Design and build ELT pipelines for data processing and analysis.
  • Construct MLOps pipelines for automated retraining and validation of models.
  • Implement CI/CD pipelines for deploying models and ML services.
  • Create services for monitoring ML models in production.

Job description

We are looking for an experienced MLOps Engineer to join our team. In this role, you will be responsible for improving pipelines for training machine learning models, processing and checking data quality, testing models and ensuring their correctness, and building model monitoring systems. The ideal candidate should be intelligent, contemplative, and composed. They should not rush through tasks, instead diving deeply into the code and being attentive to details.

WHAT YOU’LL BE DOING:

  • Design and build ELT pipelines for data processing and analysis.
  • Construct MLOps pipelines for automated retraining and validation of models.
  • Implement CI/CD pipelines for deploying models and ML services.
  • Create services for monitoring ML models in production.

WHAT WE LOOK FOR IN YOU:

  • Strong knowledge of Python
  • Familiarity with Docker.
  • Basic understanding of machine learning concepts and techniques.

WHAT WILL BE A PLUS:

  • Experience with PyTorch.
  • Familiarity with Kubernetes.
  • Knowledge of Dagster.
  • Experience with Kafka.
  • Understanding of distributed training systems for ML models.

WHY SHOULD YOU JOIN OUR TEAM?

  • Great challenges with many opportunities to prove yourself 
  • A welcoming group of highly qualified international professionals
  • Great corporate culture with internal events and surprising commitment to fostering a supportive and empowering environment
  • Cutting-edge hardware and technology
  • Comfortable Dubai, London, Malta and Mumbai offices or remotely anywhere in the world
  • 40 paid days off
  • Competitive salary
Ready to apply?
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