Software Engineer, Machine Learning
- You will be working across various NLP areas like STT, translation, summarization, sentiment analysis, TTS, and other interesting challenges that are challenging at Zoom's scale.
- Build and deploy state-of-the-art ML models for NLP use cases.
- Build large-scale training and inference pipelines
- Build and scale real-time ML services that enable Zoom’s products
- Take ML models from Research all the way to production
- Build metrics, and dashboards to measure both ML and system performance
- Work closely with the Research teams to build the required tools and services to make them productive
- Work closely with the product and operations teams to integrate ML services seamlessly into the products
- Work closely with various teams on data acquisition, cleanup, and related tooling
Why You Should Consider This Role :
- You will be a founding member of the team and have an opportunity to build/start from scratch
- An opportunity to solve some cutting-edge AI problems and deploying models that constantly advance the state of the art.
- A Flexibility in to drive the vision and direction of our products and services
- An opportunity to create an impact in the society, where billions of users will be using the final products for which the models were deployed and recommended by you
- Enjoy a great culture of inclusivity and collaboration
Qualifications
- PhD in Machine Learning, Computer Science, or related fields
- Expertise in various facets of ML and NLP, such as Automatic Speech Recognition, Speaker recognition, Machine translation, TTS
- Experience in transformers, sequence-to-sequence models
- Extensive experience with ML frameworks, strong programming skills with proven experience delivering advanced algorithmic solutions
- A passion for making ML methods robust
- Track record of driving ML research projects from start to finish. Including conception, problem definition, iteration, publication and productionization
Bonus Qualifications
- Solid software development experience
- Solid Machine Learning background and familiar with modern speech and machine learning techniques
- Strong publication record in top tier conferences such as NeurIPS, ICASSP, INTERSPEECH, TASLP, etc.
- Strong verbal and written communication skills
