DevOps Engineer with Python

Computaris

You would work on the new ML and AI platform involving several Sprint teams around the new AI/ML product. We are looking for an excellent Software Engineer experienced in high quality production Python code.  

Job Responsibilities:

  • Participate in the development of highly scalable platforms for extracting, analyzing, and processing large amounts of contextual data from a plethora of sources, both in real-time and in batch modes.
  • Craft high-performance, production-ready machine learning code for our next-generation real-time ML platform. Extend existing ML libraries and frameworks.
  • Working closely with other engineers and scientists, develop solutions to accelerate model development, validation, and experimentation cycles, and integrate models and algorithms in production systems at a very large scale.

Basic Qualifications:

  • Degree in mathematics/computer science or related discipline.
  • 7+ years of hands-on experience deploying the platforms or software at production scale
  • 7+ years of experience in the complete software development lifecycle including design, coding, code reviews, testing, build processes, deployments, and operations.
  • 3+ years of experience in Python.
  • MLOps (e.g., Kubeflow,KNative, KServe, Nvidia Triton, ML Flow)
  • Distributed Systems (e.g., Kafka, or SQS, Data Pipeline, Serverless Async system)
  • Graph (e.g., Neo4j, Cypher, Gremlin, GraphQL)
  • Cloud Infrastructure (e.g., Kubernetes, Terraform, CICD)

Preferred Qualifications:

  • MS or PhD in Computer Science or equivalent experience.
  • Experience working with large-scale distributed systems, preferably on cloud platforms (e.g., AWS, Azure, Google Cloud).
  • Experience dealing with real-world large-scale datasets.
  • Strong understanding and passion for statistical/mathematical modeling and data analysis.

E-mail:  
recruitmentmd@eu.rsystems.com

Computaris
Адрес
Кишинев
Образование
Университет, институт
Опыт работы
От 3 лет
Зарплата
Не указана
График работы
Полный день
Место работы
На территории работодателя