Machine Learning Engineer
Machine Learning Engineer
Montreal, Quebec, Canada
This job allows you to work remotely
Our client incubates and funds companies. Unconstrained by industry, they originate the ideas, hire the early teams, fund, launch, and grow each company, and maintain an integral leadership role from beginning through exit.
They have collectively raised more than $2B in venture capital and employ thousands of people. On the investment side, they are one of the most active early stage funds.
They need professionals with startup experience who can wear multiple hats in a full-stack leadership role. Someone who can take the lead of the technical team, the non-technical founders and product managers to scope, architect, and engineer their platforms.
This particular project is in the fin-tech space and focused on building the world's first Natural Language Interface for data analysis. Robust natural language understanding and semantic parsing sits at the core of their efforts to create the future of analytic tooling. They're transforming academic and lab AI experiments into enterprise-ready products.
This is an opportunity to work on the full lifecycle of an AI solution. You're going to wear many hats, research cutting-edge NLP techniques, and grapple with a variety of technical challenges in a fast-paced startup environment. They are looking for engineers who can take problems into their own hands, and prototype, iterate, and ship quickly.
In this job you will:
Follow NLP research and apply it to create a robust ensemble algorithm for translating normal English questions into executable commands (semantic parsing)
Own ML models end-to-end, from collecting training data to deploying in production
Prototype quickly with cutting edge NLP technologies
Work on grammar-based and Seq2Seq-based approaches for semantic parsing
Create the future of natural language interfaces
Must Have Skills:
2+ years industry experience working in software, machine learning, or a related field
Academic or industry experience working on machine learning – an understanding of NLP concepts (language modelling, grammar, syntactic parsing) is great, but not required.
A solid understanding of algorithmic and CS fundamentals related to Machine Learning
Experience writing maintainable, testable, production-grade code in one or more general purpose languages (Java, C/C++, Python, etc)
BS, MS or PhD in Computer Science, Engineering or a related technical field
If you're excited about their mission but don't meet 100% of the qualifications above, we still encourage you to apply.