As part of the Foundation, Search, and Voice Science team, you will design and build the next generation of SiriusXM and Pandora’s voice and search experiences. Your contributions will drive content discovery and personalization through voice and search interactions across our mobile apps, third-party devices (e.g., Alexa, Google Home, Roku, etc.), and automotive products.
As a Staff Scientist you will be an expert in areas spanning speech recognition, natural language processing and understanding, dialog management, personalization, natural language generation, and information retrieval. You will research and invent state-of-the-art solutions in these fields, help drive the scientific roadmap, mentor other scientists, and build experiences that impact over 100MM listeners. In this role you will proactively communicate and coordinate with cross-functional teams to navigate complex and uncertain environments.
Duties and Responsibilities:
- Research, design, experiment with, and build machine learning systems, particularly related to voice and search products.
- Propose, design, and analyze new experiments to validate scientific hypotheses.
- Build production data pipelines and models, and review methods and code of other scientists.
- Combined large, complex, and disparate data sets to provide product and research insights.
- Generate ideas for high-leverage, long-term projects with broad reach.
- Promote and role-model best practices of data science, engineering, and communication throughout the organization.
- Mentor and guide research and development of other scientists.
- 5+ years of research and development experience in real world NLU/P, conversational AI, chat bots, dialog management, search, or voice/dialog systems.
Requirements and General Skills:
- Demonstrated research and development in natural language processing/understanding, voice/dialog systems, or information retrieval.
- Excellent written and verbal communication skills, with the ability to effectively advocate technical solutions to scientists, engineers, and product audiences.
- Demonstrated ability to collaborate with and lead teams.
- Demonstrated ability to invent novel data science, machine learning, and engineering solutions and deploy them at scale.
- Self-motivated, growth-oriented, and driven to pursue solutions to challenging problems.
- Must have legal right to work in the U.S.
- Experience with deep learning techniques for NLP (e.g., word2vec, RNNs, transformers).
- Experience with ML-frameworks (e.g., TensorFlow, TensorFlow Serving, PyTorch, Vowpal Wabbit, scikit-learn).
- Production experience implementing machine learning pipelines and models at scale in Python, Java, Scala, or similar languages.
- Proficiency with distributed processing and warehousing frameworks (e.g., Spark, Hadoop, Hive, Tez, etc.).
- Experience with the research and development workflow/life-cycle for large-scale batch and streaming machine learning systems.
- Ability to gather stakeholder requirements and evaluate technical trade-offs.
- M.S. or Ph.D. in a quantitative field (CS, EE, Statistics, Physics, Math, Computational Linguistics, Neuroscience, etc.).
- Passion for data-driven development, reliability, and disciplined experimentation.
- Experience with any of the following:
- Cloud computing: Google Cloud Platform, Amazon Web Services, Azure
- Technologies: Kafka, Airflow, Composer
- Additional ML Concepts: Learning to Rank, Language generation, Reinforcement learning