Summer Machine Learning / Backend Engineering Internship
Summer Candidates Only, if you are looking for hire earlier, please use other posting. Thank you.
Responsibilities
- Search for new dataset material to train our ML models (finding content and derived data which can be used to build our ground truth dataset).
- Implement crawlers and data processing for those dataset collections
- Work side by side with our engineering team to integrate this software
- Implement internal tools to help augment, test, validate our datasets / models (backend and front end web development (Angular/Typescript))
- Work with data scientist to design, execute, and monitor experiments to improve our ML models
- Support ML development in production, by testing and identifying areas for improvement
- Assist in brainstorming new approaches to ML problems
- Define and manage the labeling of ground truth data by our labeling team
- Support the team by running tests on our client applications (iOS / Web)
- Support executive team with marketing collateral preparation.
Minimum Qualifications
- Pursuing CS or holding CS degree or equivalent work experience
- Related intern and or industry experience working projects
- Experience with at least one of: Node/Typescript, Python or Java languages
- Outstanding technical problem solving and debugging ability
- Self-motivated to learn and execute with attention to detail in documentation and execution
- Ability to handle technical and design ambiguity
Preferred Qualifications
- Experience with control Version / Git.
- Git workflow, Continuous Integration / Deployment: bonus points.
- Experience with software building tools like Gradle / Maven
- Experience with CI/CD frameworks
- Experience writing with command line tools
- Experience with AWS.
- Experience working remotely with an international team in different timezones.
- Experience with any/all of the following are a plus:
- Machine Learning
- Understanding of modern architectures like Convolutional Neural Networks, Transformers, Recurrent Neural Networks, etc.
- GPU or similar parallel programming architecture optimizations
- Experience with Pytorch, TensorFlow, MXNet, or a similar deep learning framework
- DevOps / Infrastructure
- Software test methodologies or QA