Build Deep learning models to understand and derive insights from unstructured data (Multi-modal - text, image, audio, etc.)
Develop custom transformer architectures to solve business problems in unstructured space.
Understand business needs and come up with an appropriate solution architecture for the use-case
Ensure deployment of ML models into production by working closely with data engineers / ML-Ops engineers.
Use of test-driven Development and code pairing practices (version control).
Collaborate with other product teams on integrations, testing and deployments.
Requirements
4 - 7 years of overall experience in machine learning with proven experience in deep learning model training and deployment
2+ Years of strong hands-on experience in PyTorch, Hugging face and good understanding of optimizers, learning rate schedulers, etc. Experience in distributed GPU compute is preferable.
4+ years of hands-on experience with Python programming language.
Ability to work well in a collaborative, agile development team with business and development partners.
Strong team player who is willing to learn, share, teach and lead depending on the situation.
Excellent problem-solving and communication skills
Good to have!
Continuously integrate and deploy developed software; modify CI/CD pipeline and scripts as necessary to improve continuous integration practices (Terraform).
Experience in Google Cloud Platform (GCS, Big Query, Cloud Run, Cloud Build, Pub/Sub)
