Location: California, United States
We are looking for a Senior Machine Learning Engineer to join our MLE team. You are someone that is passionate about leveraging technology to solve complex, real-world problems. You will train computer vision models on geospatial and satellite imagery and play a critical role in scaling our machine learning infrastructure.
- Improve our semantic segmentation and image classification models
- Train computer vision models to analyze geospatial and satellite image data
- Integrate new sources of pertinent data and information
- Understand the relationship between weathering conditions and natural sciences on property valuation & risk
- Increase efficiencies of labeling, curating, and training data
- Optimize the speed of predictions on our available GPUs
- Expand and improve our ML code base
- Lead initiatives to branch out and implement new ML systems, processes, and techniques
- Evolve our tech stack and Computer Vision techniques by implementing cutting-edge research to our problems.
- Work cross-functionally with the data engineering and data science teams
- B.S. and 5+ years of experience or an Advanced Degree and 2+ years of experience in a quantitative discipline (i.e. computer science, physics, mathematics, statistics, earth sciences, etc.)
- Deep understanding of ML design principals
- Experience training deep learning models for computer vision
- Demonstrated knowledge of ML fundamentals
- Excellent coding skills (i.e. data structures, algorithms, etc)
- Strong Python skills and experience with modern deep learning frameworks (i.e. TensorFlow/Keras, PyTorch, etc.)
- Experience with data science tools like numpy, pandas, scikit-learn, Jupyter Notebooks, etc.
- Experience writing complex SQL data queries
- Experience with cloud hosted infrastructure (i.e. AWS, GCP, or Azure), relational database tools, and git/GitHub.
Complete the form below to apply for the Computer Vision Engineer role: