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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # GCP ML Engineer (Vertex AI) - **Company:** OpenKyber LLC - **Location:** United States (Remote available) - **Experience:** Experienced - **Salary:** $174,720.0 - $195,520.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Agile Methodology, Artificial Intelligence, Microsoft Azure, Big Data, BigQuery, Continuous Integration, Data Virtualization, Apache Hadoop, IBM Cloud Computing, Python (Programming Language), OpenShift, Site Reliability Engineering Practices, Ansible, Azure Machine Learning, Systems Integration, Enterprise Data Management, Data Processing, Google Cloud, Autoscaling, Istio, Large Language Models, Fastapi, Build Management, Containerization, AI Platforms, Pyspark, Grid Computing, Machine Learning Operations, Api Design, Api Gateway, Terraform, Docker - **Published:** May 14, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=ce22f8b356b35619 ## About the Role Do you have experience in Python?, * 5+ years of Python programming and 3+ years of MLOps experience in production environments. * 5+ years with Big Data platforms such as BigQuery or Hadoop and 3+ years with PySpark. * 2+ years building APIs, preferably with FastAPI, and integrating with Google Cloud Platform/Azure or API gateways. * Expertise with containerization and orchestration including Google Cloud Platform, GKE, Red Hat OpenShift, and Docker with service mesh integration. * Hands-on experience with Vertex AI for pipelines and IBM Cloud Pak for Data for enterprise data management. * Strong understanding of LLMs and vector databases, plus working knowledge of AutoML platforms such as H2O Driverless AI or DataRobot. * Advanced IaC skills with Terraform, Helm, or Ansible for automating cloud landing zones and cluster configurations. * Proficiency in PySpark, Hadoop, or BigQuery for high-throughput data processing and vectorization pipelines. * Experience with RAG, prompt orchestration, fine-tuning, and safety/guardrails (preferred). * Deep understanding of GPU/CPU orchestration and high-performance storage for AI workloads (preferred). * Ability to lead cross-functional architecture forums and influence senior stakeholders (preferred). * Familiarity with Agile methodologies and enterprise project management tools (preferred). ## Description * Design and build scalable AI/ML platform components across on-prem and public cloud environments including Google Cloud Platform, GKE, OpenShift AI (RHOAI), and IBM Cloud Pak for Data for multi-tenant operations. * Architect hybrid CPU/GPU grid computing, object and high-performance storage, and low-latency networking to support demanding AI workloads. * Deploy and manage enterprise AI tooling including H2O AI platforms (Driverless AI) for automated model development and data virtualization. * Implement and administer Run:ai to optimize GPU/CPU utilization with high-throughput and low-latency scheduling for training and inference. * Operationalize end-to-end LLM and classical ML pipelines using Vertex AI with CI/CD, automated validation, and observability. * Build and maintain vector databases, chunking, and embedding strategies to enable RAG-based applications. * Deploy and manage Istio service mesh for secure, observable, and resilient service-to-service and AI API communication. * Apply SRE practices including circuit breakers, autoscaling, and reliability patterns to ensure system health. * Lead cross-functional architecture discussions and influence platform direction and standards. ## Related Videos - [Beyond GPT: Building Unified GenAI Platforms for the Enterprise of Tomorrow](https://www.wearedevelopers.com/videos/1525-beyond-gpt-building-unified-genai-platforms-for-the-enterprise-of-tomorrow) - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Rate-limiting using eBPF and Istio: How to protect your SaaS customers from themselves](https://www.wearedevelopers.com/videos/100220-rate-limiting-using-ebpf-and-istio-how-to-protect-your-saas-customers-from-themselves) - [How E.On productionizes its AI model & Implementation of Secure Generative AI.](https://www.wearedevelopers.com/videos/623-how-e-on-productionizes-its-ai-model-implementation-of-secure-generative-ai) - [Empowering Retail Through Applied Machine Learning](https://www.wearedevelopers.com/videos/976-empowering-retail-through-applied-machine-learning) ## Related Articles - [Got AI ideas but no money? Here are 10 free ways to level up your AI skills with Google Cloud](https://www.wearedevelopers.com/magazine/600-got-ai-ideas-but-no-money-here-are-10-free-ways-to-level-up-your-ai-skills-with-google-cloud) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [7 Cloud Computing Trends Coming in 2025 for Developers](https://www.wearedevelopers.com/magazine/412-7-cloud-computing-trends-coming-in-2025-for-developers)