Machine Learning Engineer

What you'll do

• Scope, design, and implement machine learning models for health and fitness algorithms.
• Develop multimodal fusion of sensors to track human motion and provide interpretable insights.
• Validate algorithms using synthetic data flows and real datasets with generative AI.
• Build secure and scalable systems for features on Apple Watch and iPhone.
• Apply statistical approaches to data to form hypotheses and prove results.
• Manage the computational and storage complexities associated with modeling large datasets.
• Utilize distributed compute and storage models when processing high-scale data.
• Maintain the integrity of tooling and pipelines to ensure high-quality analysis.

What we're looking for

• MS degree and 3+ years of experience in a quantitative data science discipline such as statistics, biostatistics, epidemiology, or computer science.
• Strong background in developing machine learning and/or deep learning models, preferably with time series data.
• Strong proficiency in Python and ML frameworks like PyTorch or TensorFlow.
• Ph.D or 5+ years of experience in a quantitative data science discipline (preferred).
• Ability to form hypotheses and creatively apply different statistical approaches to prove them (preferred).
• Understanding of computational and storage complexities when modeling large datasets (preferred).
• Experience leveraging distributed compute/storage models for large scale data (preferred).
• Commitment to the integrity of tooling, pipelines, and disciplined validation (preferred).