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Now Hiring: Machine Learning Resident - Advanced Tech

“If you are interested in the application of machine learning to image classification in gas emission detection, this is the right opportunity for you. Be a part of the team of research and machine learning scientists and get mentored by some of the best minds in AI.”

- Payam Mousavi, Lead Machine Learning Scientist and Mara Cairo, Product Owner, Advanced Technology

Description

About the Role

This is a paid residency that will be undertaken over a twelve-month period with the potential to be hired by our client, Kuva Canada, afterwards (note: at the discretion of the client). The resident will report to an Amii Scientist and regularly consult to and work with the Client team to share insights and engage in knowledge transfer activities.

About our Client

Kuva is leading a revolution in the detection and measurement of methane emissions for the reduction of greenhouse gas emissions in the oil & gas industry. We are providing an end-to-end solution including a cloud based emissions monitoring platform with emissions alerting service as well as a low-cost, automated infrared camera for gas detection. Leveraging our proprietary platform technology, our solution enables our customers to receive emissions alerts, reports and analytics based on images of methane emissions at the best price-performance ratio in the industry. Kuva enables the oil and gas industry to dramatically reduce emissions and at the same time improve site operations.

Kuva Canada is based in Calgary, AB and is a subsidiary of Kuva Systems, headquartered in Cambridge, MA. Applicants located in (or willing to relocate to) Alberta will be given preference, but remote applicants within Canada will be considered.

About the Project

The Kuva infrared imaging system automatically detects and measures emissions, delivering direct image-based alerts. Those images of emissions, annotated with quantified release metrics, are then transferred via the cloud to customers’ work order management and production operation systems. Armed with this actionable information, customers can implement mitigation plans without the need to conduct secondary manual inspections. An example image is shown below.

The focus of this project is to develop a machine learning solution that minimizes the occurrence of false positive detections and eliminates the need for human reviewers. Currently, relatively high false positive rates are mitigated by human reviewers that confirm the presence of gas using a diagnostic visualization of the image data. Machine learning may be able to operate on the same features used for the diagnostic image to automate much of this screening process. Kuva has a large data set of labeled data that will form the basis of algorithm development.

Required Skills / Expertise

Are you passionate about building great solutions? Do you want to drive a high impact business? You’ll be presented with opportunities to both personally and professionally develop as you build your career. We’re looking for a talented and enthusiastic individual with a solid background in machine learning, specifically computer vision.

Key Responsibilities:

  • Build, train, and evaluate ML models for detection and classification of gas emissions in multispectral imagery
  • Learn to work with multispectral image and video data to prepare them for ML training
  • Manage the productionalization and deployment of models to both cloud resources and edge devices together with Kuva
  • Undertake applied research on ML techniques to address the limitations in existing models
  • Collaborate with project team and stakeholders to develop MVP and client focused solutions
  • Participate in regular meetings with the client, preparing presentations and reports

Required Qualifications:

  • Completion of a Computing Science, Electrical Engineering (or a related graduate program) with a specialization in Computer Vision, MSc. or PhD
  • Solid understanding and experience in applications of deep learning techniques such as Convolutional neural networks, Multilayer perceptrons, sequence models (RNN, Transformers, etc.), autoencoders, etc.
  • Experience using classical computer vision tools (e.g., OpenCV, Pillow) and techniques (e.g., optical flow, segmentation, spectral analysis)
  • Proficient in developing and training deep neural network models in PyTorch and/or TensorFlow
  • Proficient in Python programming language and related ML frameworks, libraries and toolkits
  • Familiarity with Git version control and other software engineering practices and tools
  • A positive attitude towards learning and understanding a new applied domain
  • Must be legally eligible to work in Canada

Preferred Qualifications:

  • Experience with deploying neural network models to edge devices (e.g., using TensorRT or equivalent solutions)
  • Publication record in peer-reviewed academic conferences or relevant journals in machine learning (specifically machine vision)
  • Familiarity with Azure ecosystem

Non-Technical Requirements:

  • Desire to take ownership of a problem and demonstrated leadership skills
  • Interdisciplinary team player enthusiastic about working together to achieve excellence
  • Capable of critical and independent thought
  • Able to communicate technical concepts clearly and advise on the application of machine intelligence
  • Intellectual curiosity and the desire to learn new things, techniques, and technologies

Why You Should Apply

Besides gaining industry experience, additional perks include:

  • Work under the mentorship of an Amii Scientist for the duration of the project
  • Participate in professional development activities
  • Gain access to the Amii community and events
  • Get paid for your work (a fair and equitable rate of pay will be negotiated at the time of offer)
  • Build your professional network
  • The opportunity for an ongoing machine learning role at the client’s organization at the end of the term (at the client’s discretion)

How to Apply

If this sounds like the opportunity you've been waiting for, please apply by July 15! Please include your cover letter and resume with the application.

Amii is proud to be an equal opportunity employer. We are committed to creating a diverse, inclusive and excellent workforce.

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