About the Company
CGI Inc. is a global leader in IT and business consulting, committed to helping clients achieve their goals through innovative solutions. With a significant presence across Canada and around the world, we empower professionals to deliver high-quality services and advance their careers. Our Dartmouth office is a hub of innovation, serving diverse clients and fostering a collaborative environment where cutting-edge technology, including AI and Machine Learning, is at the forefront of our work.
Job Description
We are seeking a talented and motivated Machine Learning Engineer to join our dynamic team in Dartmouth, Nova Scotia. This is an exceptional opportunity for professionals looking to advance their career in AI and Machine Learning within a supportive global organization. We are proud to offer LMIA / Tier 2 Sponsorship support for eligible candidates, facilitating your transition to Canada. You will be instrumental in designing, developing, and deploying advanced machine learning models and systems that solve complex business challenges across various industries. Your work will directly contribute to driving innovation and delivering tangible value to our clients.
Key Responsibilities
- Design, develop, and implement scalable machine learning models and algorithms.
- Perform data preprocessing, feature engineering, and data quality checks to prepare data for model training.
- Collaborate with data scientists and product managers to understand business requirements and translate them into technical specifications.
- Integrate ML models into existing production systems and ensure robust, efficient, and maintainable solutions.
- Monitor, maintain, and optimize deployed models for performance, accuracy, and efficiency.
- Research and evaluate new machine learning techniques, tools, and technologies.
- Participate in code reviews and contribute to improving our MLOps practices.
- Document technical designs, processes, and results clearly and concisely.
Required Skills
- Proven experience (3+ years) as a Machine Learning Engineer or similar role.
- Strong proficiency in Python and relevant ML libraries (e.g., TensorFlow, Keras, PyTorch, scikit-learn).
- Solid understanding of machine learning algorithms, principles, and best practices.
- Experience with data manipulation and analysis tools (e.g., Pandas, SQL).
- Familiarity with software development best practices, including version control (Git).
- Excellent problem-solving skills and ability to work independently and as part of a team.
- Eligibility for LMIA / Tier 2 Sponsorship (e.g., relevant educational background and professional experience required for Canadian immigration).
- Bachelor's degree in Computer Science, Engineering, Mathematics, or a related quantitative field.
Preferred Qualifications
- Master's or Ph.D. in Computer Science, Machine Learning, or a related field.
- Experience with cloud platforms (e.g., AWS, Azure, GCP) and their ML services.
- Familiarity with MLOps tools and practices (e.g., Docker, Kubernetes, MLflow, Airflow).
- Knowledge of big data technologies (e.g., Spark, Hadoop).
- Experience with natural language processing (NLP), computer vision, or time series analysis.
- Strong communication and presentation skills.
Perks & Benefits
- Competitive salary and performance-based bonuses.
- Comprehensive health, dental, and vision insurance plans.
- Retirement savings plan with company matching.
- Generous paid time off and holidays.
- Professional development opportunities, including training and certifications.
- Relocation assistance and support for LMIA / Tier 2 sponsorship processes.
- Employee assistance program and wellness initiatives.
- Collaborative and inclusive work environment.
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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