Senior Machine Learning Engineer

2 months ago

Toronto, Ontario, Canada Perceptive Space Systems Full time
About Perceptive Space Systems

We are a cutting-edge technology company on a mission to make humanity resilient to space weather. Our innovative AI-powered space weather predictions provide the accuracy and timely actionable insights required to support today's scale, automation, and space-based operations' autonomous future.

Job Summary

We are seeking a highly motivated and self-starting Senior Machine Learning Engineer to join our team. As a key member of our engineering team, you will build the foundational technology required for satellites, launch vehicles, and human missions to operate safely and efficiently under changing space weather conditions.

Key Responsibilities
  • Provide technical leadership on machine learning projects and 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.
  • Stay updated on ML research and technologies to enhance our product offerings.
Requirements
  • MS or PhD in Computer Science or a related technical degree.
  • 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.
  • 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.
Preferred Qualifications
  • 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++.
What We Offer
  • Generous Stock Options Compensation.
  • Unlimited PTO.
  • Completely Remote (Canada).
  • Opportunities for growth and leadership.
  • Health, dental, and vision insurance.

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