Machine Learning Scientist

at  Perceptive Space Systems

Perceptive Space is on a mission to make humanity resilient to space weather. Space weather refers to changing radiation levels, magnetic fields, and other space environment conditions that impact the performance and reliability of all space-borne technological systems and endanger human health.
Current space weather predictions are limited in accuracy and do not provide the decision intelligence required to support the scale of the modern aerospace industry. This results in operational losses like premature satellite deorbit, failed launches, GPS outages, etc.
Perceptive Space is addressing this problem through its AI-powered space weather predictions, which provide the accuracy and timely actionable insights required to support today’s scale, automation, and space-based operations’ autonomous future.

REQUIREMENTS

• MS or PhD in a quantitative field (e.g., Physics, Electrical Engineering, Mathematics, Atmospheric Science).
• 3+ years of industry experience building, optimizing and deploying large-scale deep learning models.
• Demonstrate a high level of autonomy and critical thinking to take full ownership of your work.
• Track record of contributing to the successful delivery of production-ready ML models.
• Strong general foundations in software engineering -including coding standards, code reviews, source control management, build processes, and testing.
• Experience working with time-series data and scientific data
• Strong proficiency in Python and ML frameworks such as Keras, TensorFlow, and PyTorch.
• Experience with tools and frameworks like ML Flow, Ray, Dask, and Numba.
• Experience deploying ML solutions onto cloud platforms (e.g., AWS, GCP, Azure).
• Outstanding verbal and written communication skills can explain complex technical concepts to engineering peers and non-engineering stakeholders.

YOU ARE A GOOD FIT IF:

• Excited about the impact your work will have on the future of humanity.
• Want to work on challenging problems and operate outside your comfort zone in a fast-paced environment.
• Highly motivated and a self-starter who can work autonomously with minimal supervision.
• Demonstrate a ‘can-do’ attitude, always seeking innovative solutions and pushing boundaries.

OTHER REQUIREMENTS:

• To comply with Canadian 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) Compliance with these regulations will be critical to our operations and our ability to conduct business in the future. Therefore, we require that candidates must be Canadian citizens, permanent residents, or persons otherwise exempt under the CGP from accessing controlled goods in Canada.
• The role is completely remote (Canada), but candidates should be available to work during Eastern Time.

ABOUT THE ROLE

• You will build the foundational machine learning models required for satellites, launch vehicles, and human missions to operate safely and efficiently under changing space weather conditions.
• You will push the envelope of machine learning’s predictive capabilities for space weather and its impacts and redefine mission success and safety for satellite and human missions.

RESPONSIBILITIES

• Architect, build, scale, and improve ML algorithms that support our products.
• Take charge of your project end-to-end involving high ambiguity, scale, and complexity.
• Explore and research innovative machine-learning approaches to push the boundaries of what’s possible.