Data Scientist
Job in
Mississauga, Ontario, Canada
Listed on 2026-09-23
Listing for:
VDart Inc
Full Time
position Listed on 2026-09-23
Job specializations:
-
Software Development
Machine Learning/ ML Engineer, AI Engineer (Applied/Software), Data Scientist
Job Description & How to Apply Below
Data Scientist
Location:
Mississauga, ON Hybrid (2-3 Days onsite)
Mode:
Fulltime
Job Summary Seeking an AI Engineer skilled in GenAI LLMOps and MLOps to design develop and deploy scalable production grade machine learning and generative AI solutions
Job Description Design develop and deploy production grade Machine Learning and Generative AI solutions Build intelligent systems including predictive ML models covering complete model lifecycle management Develop advanced applied Large Language Model LLM applications and Retrieval Augmented Generation RAG pipelines Automate complex workflows and enhance user experiences through AI driven solutions Collaborate with cross functional teams to transition AI models from prototypes to scalable secure and high performance enterprise APIs Utilize expertise in Python programming and SQL for solution development Implement Generative AI techniques including LLMs Lang Chain Lang Graphs Claude Gemini prompt engineering and LLMOps Apply Machine Learning and Deep Learning frameworks such as PyTorch Tensor Flow Scikit Learn and XGBoost Work with vector databases like Pgvector and Chroma for efficient data retrieval Leverage distributed processing tools including Apache Spark and Apache Iceberg Employ MLOps practices for deployment using Docker Kubernetes Open Shift and FastAPI Build high performance scalable APIs with Python FastAPI to expose AI capabilities required for solutions
Roles and Responsibilities Design and implement end to end AIML solutions incorporating GenAI and LLMOps best practices
Develop and maintain scalable secure APIs for AI model deployment
Manage full ML model lifecycle including training validation deployment monitoring and retraining
Collaborate with data scientists engineers and product teams to integrate AI solutions into enterprise applications
Optimize AI workflows to ensure high performance and reliability in production environments
Stay updated with the latest advancements in Generative AI LLMOps and MLOps to continuously improve solutions
Troubleshoot and resolve issues related to AI model deployment and production systems
Document AI system architecture deployment processes and best practices
Mandatory Skills GenAI - LLMOps, Python
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