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* Principal Consultant (7083)

Systems Limited
KSA
Full-time
Senior · 5+ years experience
Onsite
Discovered 2 weeks ago
Google Cloud PlatformVertex AIPythonTensorFlowPyTorchVertex Pipelines
Free

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Google Cloud PlatformVertex AIPython
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Full Job Posting

We are seeking an experienced AI / ML Engineer to design, build, and deploy enterprise‑grade AI and machine learning solutions on Google Cloud Platform (GCP), with a strong focus on Vertex AI.

The role involves working closely with business and engineering teams to deliver impactful AI use cases across Insurance and Healthcare, including predictive models, conversational AI, and intelligent decision support systems, while ensuring compliance with PDPL and responsible AI principles.

Key Responsibilities

Design, develop, and deploy machine learning models using Google Cloud Vertex AI Build end‑to‑end ML pipelines for data preparation, training, evaluation, deployment, and serving Identify and translate business problems into AI/ML solutions (e.g., fraud detection, claims prediction, risk scoring, clinical decision support) Design and develop AI-powered features such as conversational AI, smart search, recommendations, and predictive analytics Build and integrate AI solutions using Google AI Stack, including Vertex AI, Gemini APIs, and Dialogflow CX Collaborate with Backend Engineers to expose AI models and capabilities as scalable microservices Fine‑tune and evaluate pre‑trained models and LLMs for Insurance and Healthcare use cases Implement MLOps best practices, including model versioning, CI/CD, monitoring, and automated retraining Monitor model performance and data drift; implement retraining and optimization strategies Ensure AI/ML solutions comply with PDPL, data privacy standards, and responsible AI principles (fairness, transparency, explainability) Document models, pipelines, and decisions to support auditability and explainability Requirements 5+ years of experience in AI/ML engineering, data science, or applied AI Strong hands‑on experience with GCP Vertex AI (training, pipelines, model registry, endpoints) Proficiency in Python and ML frameworks such as TensorFlow, PyTorch, or scikit‑learn Experience with MLOps tools and practices (Vertex Pipelines, Kubeflow, MLflow, CI/CD) Hands‑on experience with Google AI Stack, including Vertex AI and related services Solid understanding of model monitoring, retraining, and lifecycle management Experience with LLMs, RAG architectures, and prompt engineering Exposure to Gemini APIs and Dialogflow CX Prior experience delivering Insurance or Healthcare AI/ML solutions Knowledge of responsible AI, bias mitigation, and explainable ML techniques Experience working in regulated environments with strict data privacy requirements

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