Develop GEN AI solutions and predictive AI models, deploying them in production environments
Drive the integration of AI technologies across business operations
Collaborate with diverse teams to design solutions that deliver tangible business value through AI-driven insights
Deploy AI models into production environments, ensuring scalability, performance, and optimization
Monitor and troubleshoot deployed models and pipelines for optimal performance
Design and maintain data pipelines for efficient data collection, processing, and storage (e.g., data lakes, data warehouses)
Maintain involvement with internal and external training and relevant discussions; stay at the forefront of emerging AI techniques, tools, and trends
Collaborate with cross-functional teams to align AI projects with business requirements and strategic goals
Communicate complex AI concepts and results to non-technical stakeholders

Requirements

Bachelor’s or greater degree in Machine Learning, AI, or equivalent professional experience
Minimum of 1 year of professional experience in AI, application development, machine learning, or a similar role
Experience in model deployment, MLOps, model monitoring, and managing data/model drift
Experience with predictive AI (e.g., regression, classification, clustering) and generative AI models (e.g., GPT, Claude LLM, Stable Diffusion)
Proficiency in programming languages such as Python and SQL
Proficiency in URLs and API Endpoints, HTTP Requests, Authentication Methods, Response Types, JSON/REST, Parameters and Data Filtering, Error Handling, Debugging, Rate Limits, Tokens, Integration, and Documentation
Proficiency with cloud platforms (e.g., AWS, Azure) and big data tools (e.g., Databricks, PySpark)
Familiarity with AI frameworks such as LangChain and machine learning libraries like TensorFlow, PyTorch, and scikit-learn
Knowledge of deployment tools (e.g., Azure DevOps, Docker, AWS ECS/EKS/Fargate) and CI/CD pipelines (AWS CloudFormation, CodeDeploy)
Understanding of data engineering principles, including experience with SQL and NoSQL databases (e.g., MySQL, MongoDB, Redis)

Benefits

Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade
Company paid holidays
Personal Days
Sick Leave
Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)
Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)
Life and disability insurance
Employee assistance programs
Other benefits as provided by local policy and eligibility

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

machine learningAImodel deploymentMLOpspredictive AIgenerative AIPythonSQLdata engineeringdata pipelines

Soft Skills

collaborationcommunicationtroubleshootingproblem-solvingadaptability

Certifications

Bachelor's degree in Machine LearningBachelor's degree in AI