Machine Learning Engineer
hace 2 semanas
At Nielseniq, we are seeking a highly skilled Machine Learning Engineer to join our team. As a Machine Learning Engineer, you will be responsible for designing, developing, and managing the infrastructure to release scalable Data Science models.
Responsibilities:- Create and maintain a scalable infrastructure to deliver AI/ML processes, responding to user requests in near real-time.
- Design and implement 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.
- Work on many different software challenges, 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.
- Mentor other engineers, fostering good engineering practices across the department.
- Work closely with data scientists and end-users to ensure technical compatibility and user satisfaction.
- Work as a member of a team, encouraging team building, motivation, and cultivating effective team relations.
- Bachelor's degree in Computer Science or related field.
- Master's degree in data engineering or related.
- Demonstrated experience and knowledge in Linux and Docker containers.
- Demonstrated experience and knowledge in some of the main cloud providers (Azure, GCP or AWS).
- Proficient in programming languages: Python.
- Experience with ML/Ops technologies like Azure ML.
- Self-driven and good communication skills.
- Experience with AI/ML frameworks: Torch, Onnx, Tensorflow.
- Experience designing and implementing CICD pipelines for automation.
- Experience designing monitoring dashboards (Grafana or similar).
- Experience with container orchestrators (Kubernetes, Docker Swarm).
- Experience in using collaborative developing tools such as Git, Confluence, Jira, etc.
- Problem-solving capabilities.
- Strong ability to analyze and synthesize (good analytical and logical thinking capability).
- Proactive attitude, resolutive, used to work in a team and manage deadlines.
- Flexible work model - the team meets at the office 1 or 2 times a month.
- Our benefits include flexible working environment, volunteer time off, and employee assistance program.
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