Role: AI Engineer
Location: Mississauga, ON- Canada
Position Type: Fulltime
Client- Citi Bank
Salary- CAD 120K
Note- We have 10+ Open roles.
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- D8-10 years of relevant experience in Apps Development or systems analysis rol
- eCore AI/ML Foundations
- :Strong foundational knowledge in GenAI , Machine Learning (ML modeling), Data Science, Statistics, and AI fundamentals, including Natural Language Processing (NLP), Neural Networks, and Large Language Models (LLMs)
- .Generative AI & LLM Expertise
- :Extensive hands-on experience with leading LLMs such as Google Gemini, OpenAI models, Anthropic Claude, Mistral, Llama, and various other open-source LLMs
- .Critical: Deep working knowledge and hands-on experience with Retrieval-Augmented Generation (RAG) pipelines, including advanced RAG techniques and their detailed implementation
- .Proven ability to build, tune, and deploy LLM-based applications using platforms like Vertex AI, Hugging Face, etc
- .Expertise in developing robust prompt engineering strategies, prompt tuning, and creating reusable prompt templates
- .Hands-on experience with agentic framework-based use case implementation
- .Working knowledge of Guardrails and methodologies for assessing the performance and safety of GenAI features
- .Programming & Data Engineering
- :Strong programming proficiency in Python is a must, including extensive experience with libraries such as Pandas, NumPy, scikit-learn, PyTorch, TensorFlow, Transformers, FastAPI, Seaborn, LangChain, and LlamaIndex
- .Proficiency in integrating generative AI with enterprise applications using APIs, knowledge graphs, and orchestration tools
- .Hands-on experience with various vector databases (e.g., PG Vector, Pinecone, Mongo Atlas, Neo4j) for efficient data storage and retrieval
- .Experience in dealing with large amounts of unstructured data and designing solutions for high-throughput processing
- .Deployment & MLOps
- :Critical: Hands-on experience deploying GenAI-based models to production environments
- .Strong understanding and practical experience with MLOps principles, model evaluation, and establishing robust deployment pipelines
- .Strong expertise in CI/CD principles and tools (e.g., Jenkins, GitLab CI, Azure DevOps, ArgoCD) for automated builds, testing, and deployments
- .Cloud & Containerization
- :Proven experience with container orchestration platforms like OpenShift or Kubernetes for deploying, managing, and scaling containerized applications in a cloud-native environment
- .Soft Skills
- :Strong problem-solving abilities, excellent collaboration skills for working effectively with cross-functional teams, and the capability to work independently on complex, ambiguous problem
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