BlackBerry

Senior Machine Learning Engineer

Job description

Worker Sub-Type

Regular

Job Description

BlackBerry is looking for a Senior Machine Learning Engineer to join the Cybersecurity MLOps team. Our mandate is to develop state-of-the-art ML algorithms to solve long-standing problems in computer security, including malware detection, anomalous event/behavior detection, and user authentication. We are looking for someone who can design, develop, and execute the ML and big data pipelines needed to create the models used at the core of our Cylance Protect and Optics products. You'll work as part of a cross-functional team including researchers, big data and ML engineers, analysts, and subject matter experts.

What You'll Do
  • Design, develop, optimize, and operationalize ML models for the BlackBerry Cylance suite of cybersecurity products
  • Design, develop, and maintain big data and feature extraction/selection pipelines for model training and evaluation
  • Execute model training and evaluation pipelines and assess their outputs, using a critical eye to find errors, address gaps in performance, and ensure high product quality
  • Contribute to team meetings / discussions (sprint reviews, planning, etc)
  • Review PRs and work with team members to ensure the highest level of code and documentation quality
  • Collaborate with other teams to coordinate joint deliverables
What You Need
  • 3+ years of experience designing and building machine learning systems, both from the ground up as well as iteratively from existing code bases
  • Experience building, running, and evaluating the outputs from end-to-end machine learning pipelines, including ETL, feature extraction and selection, model development, training, evaluation, deployment, and monitoring
  • Experience with the machine learning and MLOps ecosystems (e.g. PyTorch/TensorFlow, XGBoost/LightGBM/CatBoost, scikit/numpy/pandas, MLFlow, Airflow/Prefect)
  • Experience working with big data (Spark, SQL) and cloud computing services (AWS, GCP)
  • Solid understanding of software engineering principles and best practices
  • Strong sense of ownership over the code and high standards when it comes to development, testing, and documentation
  • Ability to clearly communicate complex concepts to stakeholders and other team members with diverse backgrounds and skillsets
Scheduled Weekly Hours

40

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