Hirestarter's client is an exciting fast-moving startup in the emerging field of ML & AI located in Austin (Alegion) They prepare machine learning training data for Fortune 500, allowing you to get exposure to many different use-cases via their customers, use of best-in-class technologies and offers interesting challenges, for example, how do we efficiently exploit human-in-the-loop?
The Applied Machine Learning Engineer possesses experience in evaluating, integrating and deploying machine learning algorithms in a SaaS software platform.
The Applied Machine Learning Engineer will have responsibility for delivering an algorithmic solution to production: training, packaging in an API, performing ETL and able to being on call in case there is a need to debug.
WHAT YOU WILL DO
- Participate as a technical member of an Agile team developing company’s AI Enablement Platform and related software products.
- Decide which machine learning technologies will be used in a production environment.
- Build, train, monitor and choose the best operational architecture for machine learning production models, as well as tune and optimize existing machine learning algorithms.
- Ensure machine learning code is maintainable, scalable and debuggable.
- Integrate machine learning algorithms into the company platform.
- Collaborate with architects and software engineers on architectural reviews and design discussions.
- Work closely with the Product Owner to groom user stories, including providing implementation details, estimating effort, and contributing to acceptance criteria.
- Develop clean, well-designed, reusable, scalable code following TDD practices.
- Strive to achieve a high level of unit, integration, and acceptance test coverage.
- Pair program with fellow engineers and perform code reviews of their design and code.
- Bachelor’s or Masters degree in Engineering, Computer Science, Statistics, Mathematics or related field with coursework relevant to machine learning
- 2+ years of experience integrating machine learning algorithms into cloud platforms, including resource provisioning, installation, scaling, and validation, as well as building, training, and monitoring the machine learning production models
- Ability to being on call in case there is a problem
- Experience in developing software in Java, C++/C, and/or Python
- Experience with all or some of the following machine learning, deep learning, computer vision, image processing, and data and image analysis tools (Tensorflow, Keras, Caffe2, Torch/PyTorch OpenCV/FastCV, numpy, scipy, and scikit-learn)
- Experience with data transformations, API wrappers and output formats used with machine learning algorithms
- Hands-on, in-depth experience with AWS or other cloud infrastructure technologies
- Experience practicing OOP, TDD, CI/CD in an Agile software development environment
- Crowdsourcing experience a plus, but not required
- Start-up experience and entrepreneurial spirit highly preferred
- Excellent communication skills (verbal, written, presentation)
- Ability to handle multiple competing priorities in a fast-paced environment