Machine Learning Researcher
Location
San Francisco, CA, USA
Employment Type
Full-Time
Location Type
In-Person/Hybrid
Department
Engineering - Research
Overview
We are looking for an ML researcher who will be responsible for designing, training, and testing data pipelines and ML models while collaborating with current developers on existing models and codebases. This is a core research role that will work on expanding model offerings and updating existing models based directly on customer feedback. This role’s focus is to push the boundaries of emotion model capabilites.
This position is expected to:
Train, test, validate, and iterate on ML models for emotion detection from voice
Design and implement large data pipelines for training and evaluation
Prototype new data procesing and model approaches
Build multimodal data analysis pipelines
Incorporate customer feedback into data collection and training pipelines
Contribute to our work on bias detection and mitigation — ensuring models perform equitably across diverse populations
Work 3+ days a week in office in San Francisco
An ideal skill set includes:
A strong background in Data Science
Proficiency working with Python, Pytorch, Tensorflow/Keras, ScikitLearn, and AWS Sagemaker
Extensive experience with data processing and training models from scratch
Knowledge of architectures from simple neural networks to large scale transformer models to cutting-edge research
Familiarity with signal processing techniques and experience with time series and/or audio data
Preferred but not required:
Experience with MLOps and cloud deployment
Publications in major ML journals