Data Science Lead

Job Summary  

OODC is seeking a highly analytical and detail-oriented Machine Learning Engineer to join our team in a hybrid setup in Makati. This role is crucial for developing, deploying, and maintaining robust machine learning models, with a particular focus on the data and annotation pipelines that power them. The ideal candidate excels at rapid prototyping, possesses sharp analytical judgment to ensure data integrity, and is capable of quickly adopting new technical specifications and data taxonomies. You must be an excellent communicator, thrive in a collaborative environment, and be committed to delivering high-quality, documented work.

You’re an ideal fit if you…

• Have experience in one or more of these areas: Developing, deploying, and maintaining
  
• ML models in production; expertise in computer vision or natural language processing (NLP); and strong experience with large-scale data annotation pipelines and quality assurance.​
  
• Apply sharp analytical judgment to decide if a model's output (predictions, features) or the training data (annotations, ground truth) meet the required technical and data standards.
  
• Excel at following precise instructions and adopting new ML frameworks, algorithms, and data entity definitions/taxonomies quickly.
  
• Possess strong analytical skills for judging data usefulness, feature relevance, and model conformity to performance metrics and established specifications.
  
• Combine attention to technical and visual detail with the ability to document model architecture, data pipelines, and performance findings clearly for internal and client review.
  
• Communicate crisply in writing and thrive in multi-round, collaborative review and model refinement cycles with research and annotation teams.
  
• Have exceptional written and verbal communication skills for effectively presenting complex technical concepts
  

Requirements

• Have experience in one or more of these areas: Developing, deploying, and maintaining ML models in production; expertise in computer vision or natural language processing (NLP); and strong experience with large-scale data annotation pipelines and quality assurance.
  
• Apply sharp analytical judgment to decide if a model's output (predictions, features) or the training data (annotations, ground truth) meet the required technical and data standards.
  
• Excel at following precise instructions and adopting new ML frameworks, algorithms, and data entity definitions/taxonomies quickly.
  
• Possess strong analytical skills for judging data usefulness, feature relevance, and model conformity to performance metrics and established specifications.
  
• Combine attention to technical and visual detail with the ability to document model architecture, data pipelines, and performance findings clearly for internal and client review.
  
• Communicate crisply in writing and thrive in multi-round, collaborative review and model refinement cycles with research and annotation teams
  
• Have exceptional written and verbal communication skills for effectively presenting complex technical concepts.