Machine Learning Engineer
Last Day to Apply: March 09, 2018
We are looking for an experienced Machine Learning engineer to join our growing team. As a Machine Learning expert, you will have a unique opportunity to have high impact by advancing these systems, as well as uncovering new opportunities to apply Machine Learning to solve customer and business problems. You will also play a key role in developing tools and abstractions that our other developers will build on top of. Performs other duties as assigned.
- Improve our existing Machine Learning systems using core expertise
- Design our system for ingesting, processing, analyzing, and serving up enhanced datasets and customer insights broadly in the organization.
- Identify new opportunities to apply Machine Learning to different parts of our business.
- Take end to end ownership of Machine Learning systems - from data pipelines and training, to real-time prediction engine.
- Regular, dependable attendance & punctuality.
- Have full stack experience in data collection, aggregation, analysis, visualization, productionization, and monitoring of data science products
- BA/BS in Computer Science, Engineering or a related technical field required.
- Previous experience building end to end Machine Learning systems.
- Expert level coding and debugging skills in one or more of the following technologies: Python, R, Tensorflow
- Experience with scripting languages (Bash, Python).
- Advanced understanding of statistics, data structures, predictive algorithms and their applicability
- Creative mindset to engineer features and propose innovative ways to leverage data
- Ability to visualize data and present core insights in a clear and compelling way
- Desire to collaborate with local and remote teams
About Self Management Group
SMG is a leader in talent management solutions, partnering with clients worldwide to help them attract, select, retain, and develop top potential employees. Now the largest sales profiling company in the world, our online system is available 24/7, 365 days a year in 45 countries and in over 40 languages.
We have over 35 years ongoing research into the factors that make people successful.
Through our millions of profiles of people from over 3,500 organizations, we have developed highly sophisticated ways to measure these success factors using a variety of proprietary normative profiles.