About the Company
BlackBerry (NYSE: BB; TSX: BB) is a trusted security software and services company that provides intelligent security for things. Based in Waterloo, Ontario, BlackBerry is a leader in cybersecurity and IoT solutions, helping enterprises, governments, and critical infrastructure organizations around the world secure the IoT with next-generation technologies. With a rich history of innovation, BlackBerry is constantly evolving to tackle the most complex challenges in connected intelligence, leveraging AI and machine learning to secure the future.
Job Description
We are seeking a talented Machine Learning Engineer to join our innovative team in Waterloo, Ontario. This role is crucial for developing and deploying cutting-edge AI solutions that power our next-generation products in areas such as cybersecurity, IoT, and embedded systems. We are proud to support international talent and are offering LMIA / Tier 2 Sponsorship for qualified candidates. If you are passionate about machine learning, dedicated to solving complex problems, and eager to contribute to a global leader in secure software and services, we encourage you to apply.
Key Responsibilities
- Design, develop, and deploy machine learning models and algorithms for various applications.
- Perform data exploration, feature engineering, and model training to optimize performance.
- Collaborate with cross-functional teams including software engineers, data scientists, and product managers.
- Implement robust MLOps practices for model lifecycle management, monitoring, and retraining.
- Research and integrate new machine learning techniques and tools to enhance existing systems.
- Ensure the scalability, reliability, and security of machine learning solutions.
- Write clean, maintainable, and well-documented code.
Required Skills
- Proficiency in Python and relevant ML libraries (TensorFlow, PyTorch, Scikit-learn).
- Solid understanding of machine learning principles, algorithms (e.g., supervised, unsupervised, reinforcement learning), and statistical modeling.
- Experience with data manipulation and analysis using tools like Pandas, NumPy.
- Familiarity with cloud platforms (AWS, Azure, GCP) and MLOps practices.
- Strong problem-solving skills and ability to work with complex datasets.
- Excellent communication and collaboration skills.
Preferred Qualifications
- Master's or PhD in Computer Science, Machine Learning, Artificial Intelligence, or a related technical field.
- Experience with distributed computing frameworks (e.g., Spark, Hadoop).
- Knowledge of containerization technologies (Docker, Kubernetes).
- Experience in cybersecurity, IoT, or embedded systems domains.
- Contributions to open-source projects or relevant publications.
Perks & Benefits
- Competitive salary and performance bonuses.
- Comprehensive health, dental, and vision insurance.
- Retirement savings plan with company match.
- Generous paid time off and holidays.
- Professional development opportunities and training.
- On-site fitness center and wellness programs.
- Employee assistance program.
- Modern, collaborative office environment in a vibrant tech hub.
How to Apply
If you are interested in this position, please click the "Apply Now" button below. To ensure your application is properly considered, please prepare the following:
- An up-to-date Resume or CV
- A brief cover letter summarizing your experience and motivation
Applications are reviewed on a rolling basis. Only shortlisted candidates will be contacted for an interview.
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