Machine Learning Scientist

About Us

Perceptive Space is on a mission to make humanity resilient to space weather. Space weather refers to changing radiation levels, magnetic fields, and other conditions of the space environment. This impacts the performance and reliability of all space-borne technological systems and can endanger human health. 

Today, we rely solely on government agencies' forecasts to safeguard operations against space weather impact. These forecasts are limited in accuracy and do not provide the decision intelligence required to support the scale of the modern aerospace industry, resulting in operational losses in the form of premature deorbit of satellites, failed launches, GPS outages, etc.

Perceptive Space is addressing this problem through its AI-powered space weather prediction system, which provides the accuracy and timely actionable insights required to support today's scale, automation, and space-based operations' autonomous future. 

Backed by world-class investors and a team ​of scientists and engineers whose collective background includes NASA, Los Alamos National Lab, MIT, and Silicon Valley, Perceptive Space is transforming how aerospace and defense industries respond to the threat of space weather.

About the Role

• You will be building the foundational technology required for satellites, launch vehicles, and human missions to operate safely and efficiently under changing space weather conditions. 
• You will push the envelope of the predictive capabilities of space weather and its impacts and redefine mission success and safety for both satellite and human missions. 

Responsibilities:

• Design, implement, and evaluate efficient deep neural network architectures and algorithms for our space weather platform
• Work closely with aerospace engineers and space weather scientists to develop new benchmarks for models and datasets
• Model deployment and production: Work with software engineering to optimize and adapt models for real-time, scalable, and efficient performance
• Demonstrate a high level of autonomy and critical thinking in order to take full ownership of your work.
• Contribute to papers, patents, and publications.

Desired Skills and Experience

• An advanced degree in computer science, electrical engineering, mathematics, or another quantitative field.
• 3 years of industry experience building, optimizing, and deploying deep learning models.
• Demonstrated capability to navigate complex technical problems and to collaborate closely with cross-functional teams.
• Experience with parameter and architecture tuning of deep learning algorithms.

Regulatory Compliance Requirements: 

To comply with Canadian and United States regulations related to the space industry, candidates would need to meet specific regulatory compliance requirements in the future. 

These include, but are not limited to, the Controlled Goods Program (CGP) in Canada and the International Traffic in Arms Regulations (ITAR) in the United States. Compliance with these regulations will be critical to our operations and our ability to conduct business in the future. Therefore, we require that:

Eligibility to Work: Candidates must be legally eligible to work in Canada and/or the United States, depending on job location. Please indicate your work eligibility in your application.

CGP and ITAR Compliance:

• Candidates, if based in Canada, must be Canadian citizens, permanent residents, or persons otherwise exempt under the CGP from accessing controlled goods in Canada.
• Due to ITAR restrictions, if based in US, candidates must be U.S. persons as defined by ITAR (U.S. citizens, lawful permanent residents of the U.S., protected individuals, or certain authorized foreign nationals) or be able to obtain the required authorizations from the U.S. Department of State.

• Generous Stock Options Compensation
• Generous PTO 
• Completely Remote (Canada or US)
• Opportunities for growth and leadership within our team