Machine Learning Engineer

Confirmed live in the last 24 hours

Locations

Oakland, CA, USA • Remote

Experience Level

Entry

Junior

Mid

Senior

Expert

Desired Skills

AWS

Google Cloud Platform

Jupyter

Microsoft Azure

NumPy

Pandas

Tensorflow

Python

Requirements

M.S./Ph.D. in Computer Science or B.S. with 4+ 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
FTC toll free hotline: 877-FTC-HELP (877-382-4357)
FTC online complaint form (http://www.ftc.gov/)
Internet Fraud Complaint Center (http://www.ic3.gov/)
Non-emergency number for your local police department

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

Desired 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
Early stage growth startup experience

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 and Fierce 15 in 2023, 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.

About the Team

We’re the wearers 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 RoleYou 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 offers a holistic Total Rewards package designed to support our employees in all aspects of their life inside and outside of work. The expected base salary for this position will range from $150,000 - $210,000. Actual compensation may vary from posted base salary depending on your confirmed job-related skills and experience.

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

Qualifications

M.S./Ph.D. in Computer Science or B.S. with 4+ 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
Early stage growth startup experience

WARNING.

We have recently been made aware of online solicitations falsely using the Kintsugi name and trademarks that are pretending to hire potential applicants. This includes fake job descriptions and impersonation of our Recruitment team’s profiles.

Please only respond to messages received from the kintsugihealth.com domain. All legitimate career opportunities are posted on this page. If you’d like to flag any suspicious activity, please forward it to [email protected].

Further, if you have provided personally identifiable information (such as social security number, bank numbers or credit card information) to an unauthorized party, please contact one of the following agencies to report this disclosure and receive guidance on any further actions you should take to protect your identity:

FTC toll free hotline: 877-FTC-HELP (877-382-4357)
FTC online complaint form (http://www.ftc.gov/)
Internet Fraud Complaint Center (http://www.ic3.gov/)
Non-emergency number for your local police department.

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.

11-50 employees

Website

Novel voice biomarker software