Machine Learning Scientist at integrate.ai
🇨🇦 (Posted May 19 2019)
About the company
At integrate.ai, our mission is to build a future in which AI enriches people’s lives while creating better, more valuable businesses. Our AI-powered platform helps B2C enterprises become customer-centric, identifying what customers value in businesses and applying AI to guide customers to valuable experiences. We care about privacy and ethics, and are working to make Responsible AI a reality across consumer enterprise. We are proudly based in downtown Toronto, Canada at the center of an exciting AI ecosystem.
We are looking for a Machine Learning Scientist to join our client team. This role will be working to develop statistical and machine learning models to power our AI platform and making traditional businesses customer centric using artificial intelligence. This is a unique opportunity for someone who wants to grow in the world of machine learning and work with a team of passionate individuals committed to the mission of bringing ML to enterprise. This role will play a key role in the development of what makes our platform unique and push our science team to build new and innovative machine learning models.
What you will be doing:
Researching, developing, and validating generalizable models to power the platform capabilities and automate client-facing business processes.
Researching and developing innovative methods to better facilitate a wide-variety of machine learning tasks including feature engineering and selection, hyperparameter tuning, and optimization.
Researching and developing unsupervised machine learning methods to discover behavioural patterns across multiple datasets using representation learning, transfer learning, deep nets, etc.
Working with business stakeholders and product managers to translate product requirements into machine learning research and development activities.
Working with architects, data and quality assurance engineers to develop statistical inference processes, monitoring and testing automation frameworks to ensure data, insights, and model quality while delivering analytical insights into the product.
Skills & requirements
2+ years of hands-on machine learning experience, ideally in a high growth software development environment.
Experience in developing machine learning models and machine learning frameworks that have had impact in real life production
Experience in one or more of the following fields: NLP, image annotation, video segmentation, quantum computing, Combinatorics
Experience in transfer learning, representation learning, and domain adaptation
A Masters or PhD in Machine Learning, Applied Statistics, Computer Science, or a related quantitative discipline.
Understanding of statistical modeling and machine learning.
Deep understanding of Deep Learning, or Reinforcement Learning, or Optimization Techniques
Passion about deriving insights from large datasets and communicating those insights to clients, product managers and engineers.
Experience in the use of statistical analysis and machine learning tools, packages and languages such as TensorFlow, Python, Spark MLlib, MXNet, Theano, and PyTorch.