Senior Machine Learning Engineer

Key Skills

Aartificial intelligence, Apache Airflow, AWS, Big Data Technology, Cyber Security, Design, ETL frameworks, Google Cloud Platform (GCP), LightGBM, Machine learning techniques, MLflow, MLOps tools, NumPy, Pandas, PyTorch, Scikit-learn, SPARK Programming, SQL, TensorFlow, XGBoost

Job Description

Among the first to market with full seventh generation AI for cybersecurity, BlackBerry Spark helps users understand risks and make intelligent decisions to mitigate them before they happen. Today BlackBerry secures 96% of the threat landscape, preventing more than 165 million cyberattacks in 2021 alone. Named by Cybersecurity Ventures as 1 of the top 150 companies to watch, we securely connect more than 500 million mobile, desktop and IoT endpoint devices for G7 governments, 9/10 global financial institutions as well as the largest global aerospace, defense, healthcare, automotive and media companies.

Chances are, we are more a part of your life today than we ever were as a handset company.

Come join us as we deliver ‘Intelligent Security. Everywhere.’

Are you the person we are looking for? A Senior Machine Learning Engineer

In new product design roles: develops and programs integrated software algorithms to structure, analyze and leverage data in product and systems applications in both structured and unstructured environments. Develops and communicates descriptive, diagnostic, predictive and prescriptive insights/algorithms. In product/systems improvement projects: uses machine language and statistical modeling techniques such as decision trees, logistic regression, Bayesian analysis and others to develop and evaluate algorithms to improve product/system performance, quality, data management and accuracy. In both theoretical development environments and specific product design, implementation and improvement environments, uses current programming language and technologies to translate algorithms and technical specifications into code. Completes programming and implements efficiencies, performs testing and debugging. Completes documentation and procedures for installation and maintenance. Applies deep learning technologies to give computers the capability to visualize, learn and respond to complex situations. Adapts machine learning to areas such as virtual reality, augmented reality, artificial intelligence, robotics and other products that allow users to have an interactive experience. Can work with large scale computing frameworks, data analysis systems and modeling environments.

BlackBerry is looking for a Senior Machine Learning Engineer to join the Cybersecurity MLOps team. Our mandate is to develop innovative 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 complete 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 multi-functional team including researchers, big data and ML engineers, analysts, and domain 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
• Implement 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 work you're doing

What You Need:

• Proven 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 standard methodologies
• 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 abilities

An Absolute Commitment to Equality

BlackBerry ensures an equal employment opportunity without discrimination or harassment based on race, colour, creed, religion, national origin, alienage or citizenship, status, age, sex, sexual orientation, gender identity or expression, marital or domestic/civil partnership status, disability, veteran status, genetic information, or any other basis protected by law.

EEO/Women/Protected Veteran/Disabled

BlackBerry strives to create an accessible and inclusive application and selection process and is committed to working with and providing reasonable accommodation to job applicants who may require provisions to participate in the selection process. Should you require an accommodation, please contact recruitment@blackberry.com to discuss your needs.