Noze has digitized the sense of smell. We’ve done for the nose what the camera did for the eyes and the microphone did for the ears. It took six years and some help from NASA but we did it. Now it’s time for us to bring it to the world.
People who succeed at Noze have a sense of urgency, a ton of initiative, infinite curiosity, strong internal drive, and an enthusiasm for bleeding edge tech. This is a great opportunity to put your expertise into practice on exciting real-world problems and datasets with lots of character and, ehm, unique smells! Come join us and help make a positive impact by pushing the boundaries of precision agriculture, farming and healthcare while working with a truly multidisciplinary team.
We are looking for an AI Research Developer to join our research team, bringing in expertise and hands-on experience with implementation, experimentation and model tracking for AI/Deep learning models. In this role you will:
- collaborate with researchers to realize our vision of building a context agnostic and data-efficient AI Engine to digitize the sense of smell, being mindful of scalability, and performance optimization for building real time prediction engines.
- support the ML Engineering teams and data collection lab with R&D requirements, building solutions on sequential data collected from our sensors with the goal of identifying patterns corresponding to volatile compounds (odors) of interest.
- document the observations, methods and processes in the form of reusable internal documents and intellectual properties;
This could be the place where you can utilize your experience to have a direct impact on the growth and development of our intellectual properties and products.
What you need
- Master's (required) or PhD degree (preferred) in Computer Science, applied mathematics, or related fields.
- Experience collaborating with AI/ML researchers in an industrial environment on design and implementation of deep learning architectures in at least one framework such as Tensorflow or Pytorch.
- 3-5 years of working experience and the discipline required for experiment design, benchmarking, hyperparameter optimization, code versioning, model tracking, etc.
- Familiarity with basic concepts in ML and Neural networks such as
- Capacity design (choice of architectures, activation functions, regularizers);
- Attention and imagination mechanisms;
- Autoencoders and generative models.
- A passion for problem solving with an analytical mindset, and the drive to turn every stone to find solutions with curiosity and a deep sense of ownership.
- Being comfortable with uncertainty, agility, and the startup all-hands-on-the-deck culture.
- On site availability in Montreal for about 30% of the time.
What we offer
- The opportunity to join a forward-thinking company surrounded by a collaborative team of innovative thinkers.
- A rewarding career path with diverse opportunities for professional growth;
- A competitive compensation and benefits package including employer paid health and dental benefits.
- Learning and development budget to attend conferences, classes and other professional development events;
- A bunch of other perks that involve food, fun and travel.