- 8-10 years of relevant experience in Apps Development or systems analysis role
- 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).
- 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.
- 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.
- 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.
- Proven experience with container orchestration platforms like OpenShift or Kubernetes for deploying, managing, and scaling containerized applications in a cloud‑native environment.
- Strong problem‑solving abilities, excellent collaboration skills for working effectively with cross‑functional teams, and the capability to work independently on complex, ambiguous problems.
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Artificial Intelligence Engineer in Mississauga employer: Tekshapers
At Tekshapers, we pride ourselves on fostering a collaborative and innovative work culture that empowers our employees to excel in their roles. As a Frontend Lead, you will not only have the opportunity to shape cutting-edge web applications but also mentor the next generation of engineers, all while enjoying a supportive environment that prioritizes professional growth and development. Located in a vibrant tech hub, we offer competitive benefits and a dynamic atmosphere that encourages creativity and teamwork.
