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Senior MLOps Engineer

IT Genetics Romania

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Location:
Romania , Bucharest

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Category:
IT - Software Development

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Contract Type:
Not provided

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Salary:

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Job Description:

If you’re passionate about scalability, automated deployment, and well-optimized infrastructure, we want you on the IT Genetics development team!

Job Responsibility:

  • Design end-to-end architecture for the automated training of ML models
  • Create data pipelines to build relevant datasets and data annotation flows
  • Monitor ML model performance and data drift
  • Handle versioning, deployment, and integration with the software team
  • Develop and manage CI/CD pipelines for building, testing, and deploying models
  • Apply best practices for model versioning, rollback, and A/B testing to ensure reliable and accurate production releases
  • Set up a robust monitoring system and develop automated alerting solutions to proactively identify issues in data pipelines, model training, validation, and data variation
  • Promote MLOps best practices (Infrastructure as Code, reproducibility, security) and continuously improve internal processes to increase reliability and efficiency
  • Research and implement cutting-edge technologies to improve training efficiency (e.g., distributed training, HPC, multi-GPU strategies) for the research team
  • Explore future MLOps frameworks and GPU-based cloud solutions as part of the scalability roadmap
  • Collaborate with product managers and software engineers to identify AI/ML opportunities and develop innovative solutions

Requirements:

  • University degree, preferably in engineering (software, industrial, mechanical, process) or a related field
  • Over 5 years of experience in MLOps or machine learning engineering, with a focus on deploying and managing deep learning models at scale
  • Strong skills in Python, CI/CD pipelines, and ML frameworks (e.g., PyTorch, TensorFlow, OpenCV) for automating and scaling ML workflows
  • Expertise in monitoring and alert automation for ML workflows, including data pipelines, training processes, and model performance (e.g., Prometheus, Grafana)
  • Familiarity with distributed training techniques, multi-GPU strategies, and hardware optimization for deep learning
  • Strong communication and interpersonal skills
What we offer:
  • Meal tickets
  • A place where your voice truly matters
  • Performance bonuses
  • A day off on your birthday
  • Private medical subscription
  • Trainings and learning resources
  • Hybrid work model
  • Bookster subscription
  • A friendly, passionate, and solution-oriented team
  • Opportunities to grow or change your role within the company

Additional Information:

Job Posted:
January 01, 2026

Work Type:
Hybrid work
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