Job opportunity
Senior Machine Learning AI Engineer
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Python, machine learning, and generative AI define this Senior Consultant opportunity in Vancouver. Build production-ready solutions across Azure, GCP, and AWS.
The global professional services firm’s Data & AI practice delivers client-facing ML/AI engineering for complex business challenges. You will design end-to-end solutions, develop models, and operationalize pipelines using cloud platforms and MLOps practices. The work spans forecasting, classification, recommendation, anomaly detection, and GenAI.
Key Responsibilities:
Partner with clients to identify high-impact AI and analytics use cases
Translate requirements into end-to-end ML/AI solution designs
Develop models using Python, scikit-learn, TensorFlow, and PyTorch
Build GenAI solutions with Azure, GCP, and AWS platforms
Deploy, monitor, tune, and retrain production models
Requirements:
University degree in a relevant technical or quantitative field
Three or more years delivering production machine learning solutions
Strong Python, statistics, model evaluation, and feature engineering skills
Experience with ML frameworks, pipelines, MLOps, and cloud deployment
Generative AI, LLM, prompt engineering, or RAG experience
Apply machine learning engineering, cloud deployment, and responsible AI expertise to client solutions in Vancouver’s Data & AI practice.
#J-18808-Ljbffr
Apply on source site The global professional services firm’s Data & AI practice delivers client-facing ML/AI engineering for complex business challenges. You will design end-to-end solutions, develop models, and operationalize pipelines using cloud platforms and MLOps practices. The work spans forecasting, classification, recommendation, anomaly detection, and GenAI.
Key Responsibilities:
Partner with clients to identify high-impact AI and analytics use cases
Translate requirements into end-to-end ML/AI solution designs
Develop models using Python, scikit-learn, TensorFlow, and PyTorch
Build GenAI solutions with Azure, GCP, and AWS platforms
Deploy, monitor, tune, and retrain production models
Requirements:
University degree in a relevant technical or quantitative field
Three or more years delivering production machine learning solutions
Strong Python, statistics, model evaluation, and feature engineering skills
Experience with ML frameworks, pipelines, MLOps, and cloud deployment
Generative AI, LLM, prompt engineering, or RAG experience
Apply machine learning engineering, cloud deployment, and responsible AI expertise to client solutions in Vancouver’s Data & AI practice.
#J-18808-Ljbffr