Senior Machine Learning Engineer

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. This can 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 in the form of 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.

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

About the Role

• You will build 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 satellite and human missions.

Responsibilities:

• Provide technical leadership on machine learning projects.
• Drive new ML initiatives from concept to execution.
• Architect, build, scale, and improve ML algorithms that support our products.
• Design, develop, and optimize services and systems for training, deploying, serving, and monitoring models.
• Handle complex and large datasets to be ingested by our training and inference pipelines. This may range from analysis and interpretation to setting up the infrastructure and software to ensure low-latency throughput.
• Stay updated on ML research and technologies to enhance our product offerings.

You are a good fit if:

• Highly motivated and self-starting; able to perform duties autonomously without supervision.
• Demonstrate a 'can-do' attitude, always seeking innovative solutions and pushing boundaries.
• Understand that the goal is not to use the most complex algorithm but to bring real value to our customers.

• MS or PhD in Computer Science or a related technical degree (e.g. Mathematics, Physics, Electrical Engineering).
• 4+ years of experience as a Machine Learning Scientist or Machine Learning Engineer.
• Proven experience in providing technical leadership on complex projects.
• Track record of contributing to the successful delivery of robust, scalable, and production-ready ML models, with a focus on optimizing performance and efficiency.
• Experience building, tuning, and deploying large-scale machine learning systems with feedback loops for continuous improvement.
• Knowledge of model interpretability and explainability techniques.
• Strong proficiency in Python and ML frameworks such as Keras, TensorFlow, and PyTorch.
• Experience with ML Ops tools and frameworks such as Sagemaker, Pyspark, ML Flow, W&B, and parallel and distributed computing tools like Ray, Dask, and Numba.
• Experience deploying ML solutions with multiple cloud platforms (e.g., AWS, GCP, Azure).
• Outstanding verbal and written communication skills, capable of explaining complex technical concepts to engineering peers and non-engineering stakeholders.

An ideal candidate also has:

• Startup experience.
• Experience building, deploying, and optimizing ML models on edge devices.
• Experience optimizing distributed model training with GPU resources.
• Experience working with time-series data.
• Proficiency in C++.

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 on Eastern Time.

• Generous Stock Options Compensation
• Unlimited PTO
• Completely Remote (Canada)
• Opportunities for growth and leadership
• Health, dental and vision insurance