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Strong brand, mid-level generalist AI role, metro location, broad GenAI/MLOps requirements.
Skills are transferable across industries but require GenAI, MLOps and cloud production experience.
Explicit 3+ years plus mandatory ML/GenAI, GCP, production MLOps and deployment experience.
Design, build, and deploy AI/ML solutions including classical machine learning models and advanced Generative AI workflows on Google Cloud Platform.
Develop production-ready AI agents with multi-step reasoning and integration capabilities; build scalable data and ML pipelines for automation.
Influence architectural decisions and product strategy; implement MLOps for model monitoring, governance, and reliability in production environments.
Bachelor’s Degree in Computer Science, Data Science, Statistics, or related technical field.
Minimum 3 years of professional experience in AI/ML engineering or software engineering focused on model deployment.
Proficiency in Python, machine learning frameworks (scikit-learn, XGBoost, PyTorch/TensorFlow), and Generative AI orchestration frameworks (LangChain, LlamaIndex, AutoGen).
Working knowledge of Google Cloud Platform services including Vertex AI, BigQuery, and Cloud Run.
Experienced in taking AI agents or ML models from prototype to stable, monitored production environments indicating strong operational and delivery capability.
Comfortable engaging in architectural decisions and product strategy, highlighting a strategic and technical leadership mindset.
Skilled in cloud-native engineering practices including IaC (Terraform) and CI/CD pipeline automation (Tekton or similar), emphasizing full-stack ownership and scalability.