Machine Learning Engineer állás

Megjelenés dátuma: 2025. január 17.

Kövess minket!


Azonosító: 13072 Helyszín: Budapest Munkakör: Gépi tanulási mérnök

Our client is a global technology company. Due to expansion, they are building an IT team in their Budapest office. We are looking for a new colleague for the position of Machine Learning Engineer to join this team.

Responsibilities:

  • Automate model training, evaluation, and deployment processes in development environments.
  • Build and maintain CI/CD pipelines specifically for model training and evaluation.
  • Ensure proper documentation for all tools, CI/CD pipelines, containers, and reusable code to maintain clarity and ease of use for future team members.
  • Document best practices and guidelines for integrating new models into the workflow.
  • Support continuous model retraining and monitoring efforts in collaboration with data scientists.
  • Extend and maintain available containers that are compatible with different stages of deployment (training, testing, etc.).
  • Work closely with the software team responsible for putting model artifacts into the production pipeline, ensuring a smooth handoff of model outputs.
  • Maintain and continuously refactor reusable training/evaluation code, ensuring modularity and scalability.
  • Design and implement tools to support ML workflows, such as monitoring tools or visualization aids.

Qualifications and Skills:

  • Bachelors or Masters degree in Computer Science, Engineering, or Data Science.
  • 5+ years of experience in machine learning engineering.
  • Proven experience in building, maintaining, and automating CI/CD pipelines for machine learning projects.
  • Experience with model deployment and monitoring using AWS services.
  • Familiarity with cloud-based machine learning workflows and infrastructure.
  • Strong proficiency in Python, Bash, and Shell scripting for automation.
  • Proficient in frameworks like TensorFlow, PyTorch, and Scikit-learn for model training and evaluation.
  • Hands-on experience with AWS services Amazon S3, Amazon SageMaker, AWS Lambda, Amazon ECS/EKS.
  • Experience with Docker for the containerization of ML workloads.

Nice to Haves:

  • Knowledge of AWS Step Functions for orchestrating serverless workflows.
  • Familiarity with Terraform for managing AWS infrastructure as code.
  • Experience with distributed training.

What they offer:

  • Bonus An annual performance-based bonus
  • SZÉP Card
  • Medicover health insurance
  • Home office (opportunity to work mostly remote)

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