Summary:

　　The Generatlve AI Org at Meta builds industry leading LLM Foundation models to enable many Meta products and open source. As an Applied Research Scientist in Generative AI, you have the opportunity to help push state of the art research, build industry leading foundation models, and bring them to products to impact billions of users.GenAI Audio 's mission is to build industry leading Speech & Audio foundation models, to enable Meta products. Our current focus is on controllable generative speech synthesis, to give our AI agents human-like voices.The current status:We have built a Speech foundation model that is capable of generating high quality voice given 10 - 20 seconds of target speaker voice, and can support deep cloning with 30 - 60 minutes voices.

　　Required Skills:

　　Research Scientist, Generative AI - Speech & Audio Responsibilities:

　　Independently design and implement algorithms, train state of the art speech recognition models on large data, and evaluate their performance.

　　Perform research to tackle unsolved real-world problems and push state of the art speech recognition.

　　Develop machine learning models for both server-based and embedded systems.

　　Contribute research that can be applied to Meta product development.

　　Minimum Qualifications:

　　Minimum Qualifications:

　　Has PhD in the field of Artificial Intelligence, a related field, or equivalent practical experience. Degree must be completed prior to joining Meta.

　　Research experience in one or more of these areas: speech recognition, speech processing, machine learning, deep learning, or related fields.

　　Experience with development and implementation of speech recognition algorithm/systems and model training.

　　Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.

　　Knowledge of deep learning and neural networks.

　　Experience working with machine learning libraries like Pytorch, Tensorflow, etc.

　　Familiar with scripting languages such as Python and shell scripts.

　　Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment.

　　Preferred Qualifications:

　　Preferred Qualifications:

　　Experience with developing scalable machine learning models in at least one of the following areas: automatic speech recognition, speech synthesis, LLM, or relevant areas.

　　Experience with large scale model training, implementing algorithms, and evaluating Speech systems.

　　Proven track record of achieving significant results as demonstrated by publications at leading workshops, journals or conferences such as ICASSP, INTERSPEECH, or similar.

　　Experience taking ideas from research to production.

　　Experience solving complex problems and comparing alternative solutions, tradeoffs, and diverse points of view to determine a path forward.

　　Experience working and communicating cross functionally in a team environment.

　　Public Compensation:

　　$143,000/year to $208,000/year + bonus + equity + benefits

　　Industry: Internet

　　Equal Opportunity:

　　Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.

　　Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at [email protected].