RESPONSIBILITIES
Model Evaluation
Work closely with the research team to evaluate model performance and define optimal operating points using precision, recall, and other ML evaluation metrics.
Annotation Management
Be the focal point for annotation processes to ensure high-quality labeled data and streamlined workflows.
Database Management
Manage and maintain internal research databases for data-driven decision-making.
Cloud Infrastructure
Develop, maintain, and optimize cloud-based data infrastructure (AWS, GCP).
Benchmarking Framework
Build and maintain a benchmarking framework for continuous algorithm performance evaluation, including human-in-the-loop pipelines.
Dataset Curation
Curate training and testing datasets by querying databases and annotations, and by running data quality and auto-labelling tools.
Model Execution
Run algorithms and deep-learning models at scale.
BA in computer science or other exact science/engineering
3-5 years of experience
Strong understanding of machine learning concepts and model evaluation techniques, and Computer Vision.
Experience with database management (SQL, NoSQL) and large-scale data processing.
Familiarity with data annotation processes and experience managing labeling teams.
Proficiency in Python and SQL for data manipulation and analysis.
Strong problem-solving skills and ability to work in cross-functional teams.
Experience working with cloud-based data infrastructure (AWS, GCP, or Azure), including provisioning machines for development and multi-GPU training.
Familiarity with data engineering and analytics tools such as Databricks, Spark, and other cloud-based platforms.
