Job Description: AI Developer – AI/ML, Python, LangChain, NLP, LLM
Location: Toronto, ON (Hybrid – 4 days/week onsite)
Duration: 12 Months
Role Overview
The Senior AI Engineer will be responsible for developing, optimizing, and deploying cutting-edge AI and machine learning solutions. This role involves building scalable ML pipelines, integrating AI models into production environments, collaborating with cross-functional Agile teams, and driving innovation through modern AI technologies.
Key Responsibilities
- Develop and optimize machine learning models for business use cases such as:
- Document automation
- Customer segmentation
- Risk assessment
- Design, build, and maintain scalable ML pipelines for production deployment.
- Ensure reliable, scalable, and high-performing AI model deployments with minimal downtime.
- Collaborate with Product Owners, Data Scientists, Software Engineers, Designers, Quality Engineers, and ML Engineers within Agile squads.
- Build and maintain CI/CD pipelines for machine learning model lifecycle management, including testing, versioning, and deployment.
- Monitor production models for:
- Performance
- Accuracy
- Fairness
- Model drift
- Bias detection
- Create and maintain technical documentation for models, pipelines, and engineering processes.
- Participate in Site Reliability Engineering (SRE) activities to support production applications.
- Provide after-hours production support when required.
- Improve operational efficiency by implementing engineering best practices, monitoring, metrics, and maintaining Service Level Agreements (SLAs).
- Stay current with emerging AI/ML technologies and share knowledge across engineering teams.
Required Skills & Qualifications
Programming & Software Engineering
- Strong programming experience in:
- Experience with software development best practices and Agile methodologies.
Cloud & MLOps
- Experience working with cloud platforms:
- AWS
- Microsoft Azure
- Google Cloud Platform (GCP)
- Experience with MLOps tools and production ML deployment.
Machine Learning & AI
- 2+ years of hands-on experience developing and optimizing machine learning models.
- Strong understanding of advanced machine learning algorithms and techniques.
- Experience building and deploying production-grade ML solutions.
Large Language Models (LLMs)
- Hands-on experience with:
- LangChain
- Hugging Face Transformers
- OpenAI APIs
- Experience integrating LLMs into enterprise applications.
- Experience evaluating LLM performance using appropriate metrics.
Natural Language Processing (NLP)
- Strong understanding of NLP concepts, including:
- Named Entity Recognition (NER)
- Text Summarization
- Text Classification
- Information Extraction
Preferred Experience
- Production monitoring and model lifecycle management.
- CI/CD automation for ML applications.
- Model governance, fairness, and bias monitoring.
- Site Reliability Engineering (SRE) practices.
- Cross-functional collaboration in Agile development environments.
