Job Description
Job Overview:
- Hiring Company: Kintsugi Mindful Wellness, Inc.
- Company Website: https://www.kintsugihealth.com/
- Remote Locations: United States
- Job Type: Remote, Full-Time
About Kintsugi
Kintsugi is on a mission to scale access to mental healthcare for all. We are developing novel voice biomarker software to detect signs of depression and anxiety from short clips of free form speech. Awarded multiple distinctions for AI technology and recently named one of Forbes’ Top 50 AI companies to watch in 2022, Kintsugi helps to close mental health care gaps across risk-bearing health systems, ultimately saving time and lives.
At Kintsugi, we believe that mental health is just as important as physical health. We exist to ensure that everyone who needs mental healthcare has access to the right care at the right time.
See mental health differently with Kintsugi.
To learn more: https://www.kintsugihealth.com
About the Team
We’re the wearer of many hats dedicated to helping communities find access to mental health. Our mission is ambitious, and each member of our team has an important role to play in helping us realize it. Meet some of the team members who you will learn and grow alongside here.
The Role
You will be part of the Machine Learning (ML) team and contribute to building robust, production-ready models. You will leverage our extensive speech dataset while experimenting with a multitude of deep-learning architectures to explore state-of-the-art speech analysis methods to solve a variety of classification and regression tasks. Working alongside our cloud engineering team, you will help deploy these models and ensure they stay performant in a wide range of customer-facing applications.
Kintsugi on Diversity
Kintsugi Mindful Wellness, Inc. is an equal opportunity employer, and we value diversity in all its forms. We do not discriminate on the basis of race, religion, color, national origin, gender identity, sex, sexual orientation, gender identity, age, marital status, genetic information, veteran or disability status.
We are committed to recruit, hire, and develop an exceptional team of individuals aligned by a common vision of the future of computing. We recognize that our team is strongest when we respect and embrace differences while cultivating a culture of inclusion across race, gender, age, religion, identity, orientation, beliefs, and life experiences that make us unique. Our diversity is what drives our greatest achievements.
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.
Job Responsibilities:
- Design and implement ML models to predict signs of anxiety and depression from speech in a reproducible fashion
- Integrate with our fast paced and highly collaborative engineering and research teams to drive model compute and metric performance improvements
- Identify, evaluate and implement technologies to track and improve performance and reliability of our ML systems
- Identify sources of bias in our ML models and implement methods to ensure equitable performance
- Work with our cloud team to define requirements for production model deployment while balancing compute costs and model performance
Job Requirements:
- M.S./Ph.D. in Computer Science or equivalent or B.S. with 5+ years of experience in building production-grade machine learning models in industry and/or academic research settings
- Strong programming skills in python with extensive experience with the scientific and deep-learning stack (numpy, pandas, numba, torch, tensorflow, jupyter)
- A proven track record of building end-to-end neural network models and presenting results to colleagues
- Experience optimizing the compute performance of models for production
- Ambitious team player with strong communication skills (oral and written)
- Experience implementing and experimenting with cutting-edge ML techniques from the literature
Bonus Qualifications
- Background in speech processing or audio classification
- Experience with experiment tracking and reproducibility tools (MLFlow, WandB, DataBricks, etc)
- Experience working in a cloud environment (GCP, AWS, Azure, etc)
- Recent publication(s) in peer-reviewed AI journals
How To Apply:
Click “Apply” to fill in the application form!
More Information
- Specific Job Location United States
- Salary Offer to be discussed
- Experience Level Senior Level
- Education Level Bachelor’s Degree, Master’s Degree, Doctoral Degree
- Working Hours to be arranged (full time based )
- Job Application Via Custom Application Page