Capacity AI Engineer

3 weeks ago


Toronto, Canada Insight Global Full time

Overview Insight Global is looking for a Capacity AI Engineer who will be the AI expert who brings Generative AI, Large Language Models, and Agentic Systems to a domain-rich, data-intensive environment. The successful candidate will work alongside RF capacity engineers who deeply understand wireless networks, combining their domain expertise with your AI capabilities to build something entirely new. This will be a fully remote role across Canada and will be a 12-month contract to start, with opportunities for extension. We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to To learn more about how we collect, keep, and process your private information, please review Insight Global\'s Workforce Privacy Policy: Qualifications 5+ years of hands-on AI/ML development experience with production ML systems deployment Strong expertise in Generative AI and LLMs—experience with GPT, Claude, Llama, or similar models, including fine-tuning, prompt engineering, and RAG implementations Proficiency in Python with deep knowledge of ML frameworks (TensorFlow, PyTorch, scikit-learn) and LLM libraries (LangChain, LlamaIndex) Experience building or experimenting with agentic AI systems—autonomous agents, multi-agent frameworks, or AI decision-making applications MLOps and deployment experience—familiarity with model deployment, monitoring, and continuous improvement practices Data engineering skills—SQL proficiency, experience with data pipelines, ETL processes, and working with large datasets Cloud platform experience (GCP preferred) for ML model training and deployment Problem-solving mindset—ability to translate business needs into AI solutions and communicate technical concepts clearly Knowledge of time-series forecasting and anomaly detection Familiarity with vector databases (Pinecone, Weaviate, ChromaDB) for RAG applications Experience with multi-agent systems or agent frameworks (Pydantic AI, LangGraph, CrewAI, etc.) Understanding of explainable AI (XAI) for model interpretability Any exposure to wireless networks, telecom, or network engineering #J-18808-Ljbffr


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