Machine Learning Engineer

hace 2 semanas

Centro, España Nielseniq A tiempo completo

Analyzing, designing, developing, and managing the infrastructure to release scalable Data Science models. The ML Engineer is expected to deploy, monitor and operate production grade AI systems in a scalable, automated, and repeatable way.

Job Description
  • Create and maintain a scalable infrastructure to deliver AI/ML processes, responding to the user requests in near real time.
  • Design and implement the pipelines for training and deployment of ML models.
  • Design dashboards to monitor a system.
  • Collect metrics and create alerts based on them.
  • Design and execute performance tests.
  • Perform feasibility studies/analysis with a critical point of view.
  • Support and maintain (troubleshoot issues with data and applications).
  • Develop technical documentation for applications, including diagrams and manuals.
  • Working on many different software challenges always ensuring a combination of simplicity and maintainability within the code.
  • Contribute to architectural designs of large complexity and size, potentially involving several distinct software components.
  • Mentoring other engineers fostering good engineering practices across the department.
  • Working closely with data scientists and a variety of end-users (across diverse cultures) to ensure technical compatibility and user satisfaction.
  • Work as a member of a team, encouraging team building, motivation and cultivating effective team relations.
Qualifications

Role Requirements E=essential, P=preferred

P - Bachelor's degree in Computer Science or related field.

P - Master’s degree in data engineering or related.

E - Demonstrated experience and knowledge in Linux and Docker containers.

E - Demonstrated experience and knowledge in some of the main cloud providers (Azure, GCP or AWS).

P - Demonstrated experience and knowledge in distributed systems.

E - Proficient in programming languages: Python.

E – Experience with ML/Ops technologies like Azure ML.

E – Self-driving and good communication skills.

P – Experience with AI/ML frameworks: Torch, Onnx, Tensorflow.

E - Experience designing and implementing CICD pipelines for automation.

P - Experience designing monitoring dashboards (Grafana or similar).

P - Experience with container orchestrators (Kubernetes, Docker Swarm).

E - Experience in using collaborative developing tools such as Git, Confluence, Jira, etc.

E - Problem-solving capabilities.

E - Strong ability to analyze and synthesize (Good analytical and logical thinking capability).

E - Proactive attitude, resolutive, used to work in a team and manage deadlines.

Additional Information

Flexible work model - the Team is meeting at the office 1 or 2 times a month.

  • Flexible working environment.
  • Volunteer time off.
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