Boston, MA · Job # 8061BK
You are an engineer first and foremost, a data scientist second. You have experience working with the latest deep learning tech but always test simpler methods first and add complexity only as needed. You have experience working with unstructured text and image data. You prioritize building generalizable models over squeezing out the last tenth of a percent relative error reduction on an academic dataset. The words “big data” and “artificial general intelligence” make you cringe. You iterate quickly and design tests to validate your hypotheses. You have “real world” expertise and have worked with datasets outside of the typical academic benchmarks.
Our client company is a machine learning company turning unstructured text and image data into actionable insight. They are looking for an experienced machine learning engineer to help them solve real world problems with the latest machine learning tech.
You will be responsible for building the core machine learning tech that enables company users to draw quantitative insight from qualitative text and image data sources. You will continue to improve and iterate on their existing APIs, and help them design algorithms that enable users to build custom models without requiring hundreds of thousands of labeled examples.
- Design text and image analysis algorithms to solve novel problems
- Improve their existing machine learning algorithms to keep their tech up to date with recent advances in academia
- Design algorithms to enable users to build custom machine learning algorithms with small amounts of labeled training data
- Help the team evaluate technical efficacy of new machine learning tasks and determine what problems are appropriate fits for a machine learning solution
- 3+ years professional experience
- Experience with deep learning for analysis of text and image data
- Experience applying data science / machine learning in a practical setting
- Theano / tensorflow / torch expertise / Python experience
- ETL competency
- Eagerness to grow as a data scientist and engineer
- Expertise in transfer learning or domain adaptation problems
- Experience with web scraping or large scale data aggregation
- Competent translating academic jargon into concrete software implementation
- A habit reading arXiv like you read the morning news
- Previous expertise working on data science problems in a team environment
- Docker experience
- Data visualization expertise