✨ About The Role
- The Machine Learning Engineer will be responsible for end-to-end product development, including architecting, training, deploying, and monitoring models.
- Data processing and ML Ops will be a key focus, optimizing scalable data processing pipelines and maintaining machine learning infrastructure.
- The role involves backend integration, designing and maintaining complex workflows that leverage machine learning for automation.
- Collaboration with sales and customer success teams is necessary to respond to customer feedback and improve product offerings.
- Fine-tuning custom models for medical document understanding tasks will be a significant part of the job.
⚡ Requirements
- The ideal candidate will have at least 3 years of experience in a machine learning research or engineering role.
- A proven track record of building and maintaining scalable web applications is essential, particularly in high-volume workflow automation and data processing.
- Candidates should be able to efficiently translate open-ended problems into actionable solutions.
- Familiarity with novel NLP research ideas and techniques is important, and prior publications in top conference journals would be a plus.
- Experience in a startup environment is also advantageous, indicating adaptability and a proactive approach to challenges.