Migacore Technologies is a fast growing company that uses advanced
machine learning techniques to understand how online interactions affect
offline behavior. Our first product dramatically improves demand
forecasting for the air travel industry. Right now, 20% of airline seats
fly empty, a multi-billion-dollar inefficiency; by leveraging both
public and proprietary data to better understand when people will
travel, Migacore Technologies can increase airline revenue while also
lowering average ticket costs.
Responsibilities
Are you interested in natural language understanding, predictive
model building, structured graph mining, or applied machine learning? As
a Machine Learning Engineer at Migacore Technologies, you will be
responsible for building state-of-the-art predictive models, end to end.
You will have wide latitude to experiment with feature extraction,
model design, as well as system evaluation. There are many open-ended
questions yet to be answered, and lots of opportunity to make a lasting
impact on our product.
Requirements
- BSc, MSc, or PhD in Computer Science, Software Engineering, or equivalent experience in another quantitative field.
- Strong understanding of machine learning techniques and algorithms.
- Hands-on experience designing, building, and evaluating predictive models.
- Proficiency in Python preferred. Java/C++/Go/Ruby experience is also welcome.
- Bonus points for strong understanding of natural language processing techniques and algorithms.
- Bonus points for familiarity with TensorFlow, PyTorch, or Keras.
- Bonus points for experience building and deploying products that include a web-based user interface.
- Experience with data visualisation tools, such as D3.js, GGplot, etc.
- Tackle open-ended problems independently, and think outside the box.
- Statistical thinking.
- Strong attention to detail.
What we offer
- Competitive salary.
- Great working environment.
- A stake in the business.
- A critical position in a high-growth machine learning startup.
- The chance to move fast, deploy often, and have a real impact on the product.
- The chance to learn and grow with the company, extremely fast.
