Top Data Engineer Jobs in Portugal

The Software Engineer will manage data collection for model training, operate cloud infrastructure, and collaborate on dataset roadmaps to enhance data quality for Speechify's products.

The Software Engineer will enhance data collection for AI model training, manage cloud infrastructure on GCP, and collaborate with scientists and teams on data workflows.

The Software Engineer will handle data collection for AI model training, optimize the data ingestion pipeline, and collaborate with scientists to improve data quality and scale.

Responsible for data collection to support model training operations, extending cloud infrastructure, and collaborating with AI team on dataset roadmap.

The Software Engineer will enhance data ingestion pipelines, collaborate with AI scientists, and integrate new audio data sources, all within a cloud infrastructure.

The role involves managing data collection for AI model training at Speechify, optimizing ingestion pipelines on cloud infrastructure, and collaborating with scientists to enhance data quality and scalability.

The Software Engineer will manage data collection for model training, operate cloud infrastructure, and collaborate on AI datasets.

The Software Engineer will enhance data collection processes, manage cloud infrastructure on GCP, and collaborate with scientists on AI model datasets.

The role involves managing data collection for AI model training, extending cloud infrastructure, and collaborating on dataset roadmaps at Speechify.

The Software Engineer for Data Infrastructure & Acquisition will handle data collection for model training, manage cloud infrastructure on GCP, and collaborate with the AI team to enhance data quality and scalability.

The Software Engineer will manage data collection, optimize the ingestion pipeline on GCP, and collaborate with AI scientists to enhance datasets for model training.

The Software Engineer will enhance data collection processes, manage cloud infrastructure for ingestion pipelines, and collaborate on dataset roadmaps for AI products.

The role involves supporting data collection and ingestion pipeline operations for AI model training, including collaboration on dataset roadmap and cloud infrastructure management.

The Software Engineer will manage data collection for AI model training, extend cloud infrastructure on GCP, and collaborate on data strategy.

This Software Engineer role focuses on data collection for model training at Speechify, requiring skills in data ingestion, cloud infrastructure, and collaboration with AI team members.

As a Software Engineer on the Data team at Speechify, you'll collect audio data, manage cloud infrastructure, and collaborate on dataset roadmaps to enhance model training operations.

As a Software Engineer on the AI team, you will manage data collection, extend cloud infrastructure, and collaborate on dataset roadmaps for model training operations.

This role entails sourcing audio data, extending cloud ingestion pipelines on GCP, and collaborating with AI scientists to enhance data processing for model training.

The Software Engineer will collect data for model training, extend cloud infrastructure, and collaborate to enhance data quality and scale for AI products.

The Software Engineer will support data collection for model training by enhancing cloud infrastructure and collaborating on data workflows, focusing on efficiency and scalability.

The role involves managing data collection and infrastructure for AI model training at Speechify, focusing on scalable data processing and collaboration with the AI team.

As a Software Engineer for Data Infrastructure & Acquisition at Speechify, you will focus on data collection, operate cloud infrastructure, and collaborate with the AI team to enhance data processing for model training.

The role involves data collection for model training, managing cloud infrastructure, and collaborating on the AI team's dataset roadmap to enhance Speechify's products.

The Software Engineer will manage data collection for model training, optimize cloud infrastructure on GCP, and collaborate with AI team members to enhance dataset quality and volume.

Lead development of data pipelines, ETL, and analytics for pre- and post-silicon DFT data; apply statistical methods and applied AI/GenAI to solve EDA/DFT problems; design scalable distributed databases; collaborate across teams and mentor junior engineers.