Software Engineer, Machine Learning

Requirements

• Strong experience in machine learning, signal processing, and software development
• Experience in building and deploying models that can accurately make inference from high-frequency sensor signals
• Programming skills in languages such as Python
• Familiarity with signal processing techniques and libraries such as NumPy, SciPy, and Pandas
• Experience with data visualization tools such as Matplotlib, Seaborn, or Plotly
• Experience with ML frameworks such as TensorFlow, PyTorch, or Keras
• Understanding of machine learning concepts, including supervised and unsupervised learning, regression, classification, clustering, and dimensionality reduction
• Proven experience of working prioritizing and working efficiently, to drive the most impactful work forwards
• Proven experience with Machine Learning model pipeline, topology and architecture, hyper-parameter optimization

Nice to Haves

• Experience with wearable device data, or other low-level sensor data sources
• Experience with transfer learning, domain adaptation, and few-shot learning
• Familiarity with Explainable AI techniques and libraries such as LIME, SHAP, or TreeExplainer
• Certification in machine learning, data science, or a related field

What You'll Be Doing

• Build, iterate and optimize models and experiment to build state-of-the-art performance within wearable devices constraints
• Develop and implement data augmentation techniques to improve model performance and robustness
• Collaborate with cross-functional teams to integrate ML models into existing systems and products
• Evaluate and optimize model performance using various metrics and techniques
• Stay up-to-date with the latest advancements in machine learning and apply knowledge to improve model performance
• Document and communicate technical findings and results to stakeholders
• Participate in code reviews and contribute to best practices for ML engineering

Perks and Benefits

• Not mentioned