Location: Burlinggame, California, United States
We are a Google Ventures backed Series A start up focused on tackling the obesity epidemic using AI. We use a continuous glucose monitor to power data-driven weight loss by translating your metobolic signals into recommendations for eating, exercise, and overall better health habits.
Be part of our ML team that builds end-to-end machine learning pipelines using deep learning as well as traditional statistical learning techniques.
- Analyze, process, validate complex data sets from multiple sources such as continuous glucose monitors (CGM), wearable devices, exercise equipment sources
- Understand and interpret trends and patterns in the data
- Lead and/or contribute to ML applications in Time Series, Structured Data, Natural Language processing, or Computer Vision
- Build robust, scalable MLOps platforms using Amazon SageMaker
- Report directly to Head of ML
- 3+ years of experience in building ML models
- Proficiency in data structures, algorithms, and Python
- Proficiency in TensorFlow and/or PyTorch
- Experience with cloud platforms and ML tools: AWS/GCP, Amazon SageMaker
- Bachelor’s/Master’s degree in Computer Science, Mathematics, or a related quantitative field
Complete the form below to apply for the Lead Machine Learning engineer role: