R&D Data Engineer in AI and Computer Vision

Key Skills

Aartificial intelligence, Agile methodologies, Big Data Technology, Computer Vision (CV), Data Lake, Data Modeling, Design, DevOps, Docker, Effective communication skills, Elasticsearch, ETL/ELT technologies, Google Cloud Platform (GCP), Kubeflow, Kubernetes-K8s, Linux Operating system, MLflow, MLOps tools, Presentation skills, Python Programming, REST API, Writing

Job Description

We are looking for a dedicated, pro-active and experience R&D Data Engineer in AI and Computer Vision to join our R&D team in Eviden

Our team is building Eviden Computer Vision Platform, a real-time video analytics solution for different verticals. We use AI technologies to design and develop the product, as well as Big Data software components to manage the related data.

We are seeking a skilled and motivated Data Engineer to complete our team on end-to-end data pipeline implementation and data lake operation.

Responsibilities:

• Build and maintain robust data pipelines to ingest, transform, and load data from various sources. Ensure data quality, consistency, and reliability throughout the pipeline.
• Implement data transformation logic to clean, enrich, and transform raw data into structured formats suitable for analysis and reporting. Leverage ETL/ELT processes as needed.
• Manage the data platform infrastructure, including choosing appropriate storage technologies, optimizing storage utilization, and ensuring data accessibility.
• Implement and enforce data security measures, access controls, and compliance standards to maintain the integrity and privacy of the data.
• Develop mechanisms for efficient data search and retrieval, considering relevancy, query performance, and user experience.
• Monitor and optimize the performance of data pipelines and storage systems to ensure efficient data processing and retrieval.
• Maintain clear and comprehensive documentation of data pipeline designs, processes, and configurations to facilitate knowledge sharing and future maintenance.
• Implement workflows to automate the building, testing and deployment of data lake components following DevOps practices.
• Manage AI assets (i.e., datasets, models) in a proper and secure way.
• Integrate meta-data extraction components leveraging AI models and third party tools such as labelling frameworks.
• Collaborate effectively with cross-functional teams including data scientists, data engineers, frontend and backend developers, and product owners to align on project goals and requirements.
• Participation in European research projects.

Education:

• Bachelor's, Master's, or PhD in Computer Science, Electrical Engineering, or a related field.

Essential knowledge and professional experience:

• Proven experience (3+ years) in designing, building, and maintaining large-scale data pipelines and data lake infrastructure.
• Strong proficiency in programming languages such as Python.
• Hands-on experience in REST API development.
• Hands-on experience with Elasticsearch, including data ingestion, indexing, and search capabilities. Familiarity with Elasticsearch Query DSL and search relevancy concepts.
• Knowledge of data modelling, schema design, and ETL/ELT processes.
• Prepare software applications for their deployment using Docker and Kubernetes.
• Ability to work with software configuration management tools such as Git or GitLab.
• Knowledge of DevOps and Continuous Integration/Delivery/Deployment.
• Practice of agile methodology.
• Proficient user of Linux environments.
• English level B2

Additional knowledge:

• Experience in MLOps tools, e.g., MLFlow, Kubeflow.
• Experience with Google Cloud Platform (GCP).

Competences:

• Fluency in English and Spanish are mandatory
• Good writing and presentation skills.
• Strong personal soft skills set communicative, enthusiastic, highly collaborative, proactive, and self-driven.
• Ability and enthusiasm to learn new technologies quickly.

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Benefits:

• Half-day Fridays.

• Intensive workday in summer.
• Personalised training and upskilling programme.
• Flexible working hours and ways of working.