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Vetted Google Cloud Platform Professionals
Pre-screened and vetted.
Senior Full-Stack Software Engineer specializing in cloud storage and developer tooling
Principal Data Scientist & AI/ML Engineer specializing in LLMs, recommender systems, and MLOps
Senior Machine Learning Engineer specializing in large-scale AI systems
Senior Software Engineer specializing in AI platforms and full-stack cloud systems
Staff Software Engineer specializing in data platforms, distributed systems, and AI workflows
Senior Full-Stack Engineer specializing in integrations, microservices, and data platforms
Senior Software Engineer specializing in AI systems and real-time distributed platforms
Staff Full-Stack Software Engineer specializing in cloud platforms and real-time health data
Staff Data Scientist specializing in machine learning, deep learning, and big data
Executive AI/ML Engineer specializing in LLMs, NLP, and production ML systems
Staff Software Engineer specializing in ML infrastructure and data platforms
Senior Software Engineer specializing in cloud platforms, AI systems, and EdTech
Staff Software Engineer specializing in cloud infrastructure and AI platforms
Staff Software Engineer specializing in full-stack distributed systems
Senior AI Engineer specializing in NLP and large language models
William Christerson
Senior Software Engineer specializing in backend systems and web applications
“Engineer with startup experience building AI-powered internal knowledge and support products from ambiguous early-stage concepts into production systems used by multiple teams. Particularly strong in end-to-end LLM product delivery across backend orchestration, retrieval, observability, security, and full-stack user experience, with clear impact on productivity and self-service adoption.”
Richard Jackson
Senior Machine Learning Engineer & Solution Architect specializing in cloud AI systems
“Backend/ML platform engineer with Google experience leading Python microservices for an AI-driven recommendation/retrieval system, including PyTorch inference and a retrieval-augmented generation workflow. Strong in production Kubernetes + GitOps (ArgoCD), real-time Kafka/Spark pipelines, and phased on-prem/legacy to AWS/GCP cloud migrations with reliability-focused rollout and rollback practices.”