Machine Learning Scientist

1 Month ago • All levels • Research Development • $190,000 PA - $320,000 PA

Job Summary

Job Description

Sesame is seeking a Machine Learning Scientist to contribute to the development of their ML models across multiple modalities, focusing on NLP, Speech, and/or Computer Vision with an emphasis on deep learning. The role involves working across the ML stack, including model architectures, data curation, evaluation, training, and inference infrastructure, as well as conducting research and experimentation. Candidates should be up-to-date on recent papers and possess the creativity to develop new solutions for unique goals. The company aims to create lifelike computers and voice companions, with a team comprised of founders from Oculus and Ubiquity6, and leaders from Meta, Google, and Apple.
Must have:
  • Experience in high-ambiguity environments
  • Published papers in NLP, Speech, or Computer Vision with large-scale deep learning
  • Familiar with state-of-the-art AI
  • Bachelor's degree or higher in CS or related field
Good to have:
  • Masters/PhD
  • Experience with products
  • Experience in a startup environment
Perks:
  • 401k matching
  • 100% employer-paid health, vision, and dental benefits
  • Unlimited PTO and sick time
  • Flexible spending account matching (medical FSA)

Job Details

About Sesame

Sesame believes in a future where computers are lifelike - with the ability to see, hear, and collaborate with us in ways that feel natural and human. With this vision, we're designing a new kind of computer, focused on making voice companions part of our daily lives. Our team brings together founders from Oculus and Ubiquity6, alongside proven leaders from Meta, Google, and Apple, with deep expertise spanning hardware and software. Join us in shaping a future where computers truly come alive.

About the Role

New and novel approaches are needed to realize all of our product goals. As a Machine Learning Scientist at Sesame, you are a research-oriented person with experience in NLP, Speech, and/or Computer Vision with a focus on deep learning. You are up to date on recent papers and approaches and you have the creativity and the intuition to come up with new solutions based on the application at hand.

Responsibilities:

  • Contribute to the development of our ML models across multiple modalities.

  • Work across the ML stack, including model architectures, data curation, model evaluation, training & inference infrastructure, research, and experimentation.

  • Pick promising approaches from the literature to bet on, and create new approaches where necessary to achieve our unique goals.

Required Qualifications:

  • Experience working independently in high-ambiguity environments.

  • Published papers in NLP, Speech, or Computer Vision involving large-scale deep learning.

  • Familiar with the state of the art in AI.

  • Bachelor’s degree or higher in CS or related field.

Preferred Qualifications:

  • Masters/PhD desired.

  • Experience working with products.

  • Experience in a startup environment.

Sesame is committed to a workplace where everyone feels valued, respected, and empowered. We welcome all qualified applicants, embracing diversity in race, gender, identity, orientation, ability, and more. We provide reasonable accommodations for applicants with disabilities—contact careers@sesame.com for assistance.

Full-time Employee Benefits: 

  • 401k matching

  • 100% employer-paid health, vision, and dental benefits 

  • Unlimited PTO and sick time 

  • Flexible spending account matching (medical FSA) 

Benefits do not apply to contingent/contract workers

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About The Company

San Francisco, California, United States (On-Site)

San Francisco, California, United States (On-Site)

San Francisco, California, United States (On-Site)

San Francisco, California, United States (On-Site)

San Francisco, California, United States (On-Site)

San Francisco, California, United States (On-Site)

San Francisco, California, United States (On-Site)

San Francisco, California, United States (On-Site)

San Francisco, California, United States (On-Site)

San Francisco, California, United States (On-Site)

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