Artificial Intelligence Engineer
- Canada
Full-time
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Job details
- Job type
- Full-time
- Posting language
- English
- Posted
Original job description
Key Responsibilities
- Design, develop, train, and deploy AI and machine learning models.
- Build AI-powered applications using Python and relevant AI frameworks.
- Work with Generative AI, LLMs, and prompt engineering.
- Develop AI solutions using NLP, computer vision, and predictive analytics.
- Integrate AI models with APIs, databases, and existing applications.
- Implement Retrieval-Augmented Generation (RAG) pipelines and vector databases.
- Prepare, clean, process, and analyze large datasets.
- Evaluate model performance, accuracy, scalability, and reliability.
- Deploy and monitor AI applications in cloud environments.
- Collaborate with software engineers, data scientists, and product teams.
- Follow best practices for AI security, responsible AI, and data privacy.
Required Technical Skills
- Programming: Python, SQL, object-oriented programming.
- Machine Learning: Scikit-learn, supervised and unsupervised learning.
- Deep Learning: TensorFlow or PyTorch.
- Generative AI: LLMs, prompt engineering, RAG, AI agents.
- NLP: Text processing, embeddings, transformers.
- Frameworks: LangChain, LangGraph, or similar tools.
- Databases: SQL databases and vector databases such as FAISS, Pinecone, or Chroma.
- APIs: REST APIs, FastAPI, or Flask.
- Cloud & Deployment: AWS, Azure, or Google Cloud; Docker and CI/CD.
- Version Control: Git and GitHub.
Preferred Qualifications
- Experience building and deploying production-ready AI applications.
- Knowledge of model fine-tuning and evaluation.
- Familiarity with MLOps and model monitoring.
- Understanding of data structures, algorithms, and software engineering principles.
- A portfolio of AI projects on GitHub is an advantage.
More about this job
Responsibilities
Design, develop, train, and deploy AI and machine learning models and applications, including solutions using generative AI, NLP, computer vision, and predictive analytics. Prepare and analyze datasets, integrate models with existing systems, deploy and monitor applications in cloud environments, and follow responsible AI, security, and privacy practices.
Requirements
Requires Python, SQL, machine learning and deep learning knowledge, and experience with generative AI, LLMs, prompt engineering, RAG, NLP, and vector databases. Familiarity with APIs, cloud platforms, Docker, CI/CD, Git, and production AI deployment is expected; MLOps, model monitoring, and fine-tuning are preferred.
Skills
- Python
- SQL
- Machine Learning
- Scikit-Learn
- TensorFlow
- PyTorch
- Generative AI
- Large Language Models
- Prompt Engineering
- Retrieval-Augmented Generation
- Natural Language Processing
- Computer Vision
- LangChain
- Vector Databases
- REST APIs
- Cloud Deployment
Visa sponsorship
Not detected in the job text
Categories
- Technology
- Software
- Data & Analytics
- Engineering
- Science & Research
Keywords
- Python
- SQL
- Object-Oriented Programming
- Scikit-Learn
- Supervised Learning
- Unsupervised Learning
- TensorFlow
- PyTorch
- Generative AI
- Large Language Models
- Prompt Engineering
- AI Agents
- Retrieval-Augmented Generation
- Natural Language Processing
- Embeddings
- Transformers
- LangChain
- LangGraph
- Vector Databases
- FAISS
- Pinecone
- Chroma
- REST APIs
- FastAPI
- Flask
- AWS
- Azure
- Google Cloud
- Docker
- CI/CD