We believe everyone is born creative. We’re a diverse tapestry of thinkers, dreamers, givers, DIYers, handi-workers, artisans, and forever and always architects of things.
At Cricut, we place the power of handmade into the hands of all. We give you beautiful, easy-to-master tools so you can make something unique, remarkable, perfect. We surround you with ideas, community, inspiration, and encouragement to take your creativity further than you ever imagined. And as a community, we celebrate the exhilarating act of making every single day.
So, make that handcrafted card that feels like a hug. Design a shirt for fun, for family, or for a full-blown business. Craft with a passion or for a purpose. Make something big and bold, itsy-bitsy, amazingly ambitious, or just plain silly. Whatever you make, just make your heart out. Because here’s the remarkable truth: When we all make together, we make all things possible.
Let’s make.
- Write robust Python software code in our machine learning training repository while applying best software practices to support machine learning scientists in tasks such as fetching training data, preprocessing it, and orchestrating the training runs;
- Integrate the training software into our continuous integration cluster to support metrics persistence across experiments, weekly/nightly neural network builds, and other unit / throughput tests;
- Profile performance of training software in our training cluster, identify bottlenecks in and between CPU/GPU code execution, and work on optimizing its throughput and scalability within and across nodes to ultimately reduce convergence time;
- Coordinate with the team and managing the business requirements and also working with external development teams.
- 2+ years of Working experience as a Deep Learning Engineer or Data Scientist develop and executing computer vision deep learning model design and experimentation using Python or C++;
- Experience with Python, pandas, numpy, pytorch, scikit-learn, SQL;
- Experience with ML frameworks such as TensorFlow, MxNet, PyTorch;
- Deep knowledge of machine learning algorithms, including supervised, unsupervised, neural network, regression, and tree-based approaches;
- Experience with OpenCV;
- Familiarity with AWS tools such as SageMaker, EMR, Lambda, and Fargate a plus;
- Ability to with product managers to define achievable tasks with ML models;
- Ability to work in a fast-paced development environment;
- Good team player with great communication skills;
- Passionately motivated to take ideas from R&D phase to a product.
- Bachelor’s degree or higher in Applied Mathematics, Physics, Computer Science, Data science, Statistics, Artificial Intelligence.
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