Job Summary
We are seeking an experienced GCP AI/ML & Predictive Analytics Subject Matter Expert (SME) to design, develop, deploy, and support enterprise AI/ML and predictive analytics solutions on Google Cloud Platform (GCP). The role will provide technical leadership for AI and data science initiatives, partnering with business, engineering, architecture, and data teams to deliver scalable, secure, and production-ready solutions. The successful candidate will have strong experience in machine learning, predictive analytics, cloud-based AI/ML platforms, data engineering, and MLOps, with the ability to translate business requirements into actionable AI-driven solutions.

Key Responsibilities
 Design, develop, and implement scalable AI/ML and predictive analytics solutions using GCP.
 Lead architecture discussions and provide technical guidance for AI/ML initiatives.
 Develop, deploy, monitor, and optimize machine learning models and AI services.
 Design and implement end-to-end machine learning pipelines and MLOps processes.
 Develop predictive analytics solutions to support business decision-making and operational improvements.
 Evaluate and recommend AI/ML technologies, tools, and architectural approaches.
 Build and maintain AI/ML solutions using GCP services including Vertex AI, BigQuery, Cloud Storage, Dataflow, Dataproc, Pub/Sub, and Cloud Functions.
 Establish machine learning operational standards, governance processes, and lifecycle management practices.
 Implement model monitoring, performance tracking, validation, and retraining processes.
 Ensure scalability, reliability, performance, and maintainability of AI/ML platforms.
 Design and implement predictive analytics solutions including forecasting, recommendation systems, classification, regression, and anomaly detection.
 Perform data exploration, feature engineering, model training, evaluation, and optimization.
 Identify opportunities to leverage AI and predictive analytics to address business challenges and improve outcomes.
 Assess model performance using appropriate statistical and machine learning techniques.
 Partner with business stakeholders to understand requirements and identify AI/ML opportunities.
 Collaborate with data engineers, software engineers, architects, and product teams to deliver integrated solutions.
 Communicate technical concepts, trade-offs, and recommendations to technical and non-technical audiences.
 Mentor team members on GCP, AI/ML technologies, predictive analytics practices, and MLOps methodologies.
 Contribute to architectural standards, best practices, and reusable solution patterns.

Required Qualifications
 Bachelor's degree in Computer Science, Data Science, Engineering, Information Systems, Mathematics, Statistics, or a related field, or an equivalent combination of education, training, military experience, and relevant work experience.
 Minimum of 10 years of experience in Data Engineering, Data Science, Machine Learning, Artificial Intelligence, Analytics, or related technical disciplines.
 Experience designing, developing, deploying, and supporting enterprise AI/ML solutions.
 Experience with GCP services, including one or more of Vertex AI, BigQuery, Cloud Storage, Dataflow, Dataproc, Pub/Sub, or Cloud Functions.
 Experience developing, deploying, monitoring, and maintaining machine learning models in production environments.
 Experience building end-to-end AI/ML pipelines and implementing MLOps practices.
 Experience with predictive analytics methodologies, including forecasting, recommendation systems, classification, regression, and anomaly detection.
 Strong programming experience in Python.
 Experience with one or more machine learning frameworks such as TensorFlow, Scikit-learn, PyTorch, or equivalent frameworks.
 Knowledge of data preparation and transformation, feature engineering, model validation and testing, model performance optimization, and machine learning lifecycle management.
 Proven ability to collaborate effectively with cross-functional business and technical stakeholders.
 Strong verbal, written, and presentation communication skills.
 Ability to work from or relocate to one of the following approved locations: San Francisco Bay Area, CA; Charlotte, NC; Dallas, TX; Phoenix, AZ; or New York, NY.

Preferred Qualifications
 Experience with Generative AI, Large Language Models (LLMs), AI agents, or AI orchestration frameworks.
 Experience with data visualization and analytics tools such as Power BI, Looker, Tableau, or similar platforms.
 Experience with Kubernetes and Docker.
 Experience with CI/CD pipelines and infrastructure automation.
 Experience implementing AI governance, model risk management, or responsible AI practices.
 Experience supporting enterprise-scale AI/ML solutions in regulated environments.

Certifications
 Google Cloud Professional Machine Learning Engineer certification.
 Google Cloud Professional Data Engineer certification.
 Related cloud or AI certifications.