Company Description Tiger Analytics is a global consulting and services firm that helps organizations navigate complexity through Data and AI-led transformation. The company designs and operationalizes solutions that drive measurable value at scale, leveraging deep expertise in business value chains, agile operating models, and modern data platforms. Strategic partnerships with leading hyperscalers enable Tiger Analytics to engineer cutting-edge Data & AI solutions that move beyond standard playbooks. With a team of over 5000 technologists and consultants, the company tackles some of the toughest industry problems. Tiger Analytics offers career opportunities across multiple global offices, including the US, India, Canada, Mexico, UK, Spain, Singapore, and Australia.
Role Description This full-time AI Engineer role is based in Toronto, ON and follows a hybrid work model, combining on-site collaboration with flexible work-from-home arrangements. The AI Engineer will design, build, and deploy AI solutions, including machine learning models and neural network architectures, to address complex business challenges. Day-to-day responsibilities include data exploration and preprocessing, model training and evaluation, and integrating AI components into production-grade software systems. The role involves applying techniques such as pattern recognition and natural language processing (NLP), collaborating closely with data scientists, software engineers, and business stakeholders. The AI Engineer will also contribute to code reviews, performance optimization, documentation, and continuous improvement of AI pipelines and practices.
Qualifications
- Strong foundation in Computer Science with experience in Software Development for building, testing, and deploying AI-driven applications.
- Hands-on experience with Neural Networks and Pattern Recognition for designing and implementing machine learning solutions.
- Practical knowledge of Natural Language Processing (NLP) techniques and tools to develop language-based AI applications.
- Proficiency in programming languages commonly used in AI (such as Python or Java) and familiarity with ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
- Experience working with cloud platforms and data engineering workflows for scalable model training and deployment.
- Strong analytical and problem-solving skills, with the ability to translate business requirements into technical solutions.
- Effective communication and collaboration skills for working in cross-functional, hybrid teams.
- Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field; relevant industry experience in AI/ML is highly valued.
