> Markdown version of [/jobs/ext/169312-gcp-ml-engineer-vertex-ai](https://www.wearedevelopers.com/jobs/ext/169312-gcp-ml-engineer-vertex-ai). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # GCP ML Engineer (Vertex AI) - **Company:** OpenKyber LLC - **Location:** Wilmington, United States (Remote available) - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Artificial Neural Networks, Computer Programming, Continuous Integration, Distributed Systems, Python (Programming Language), Open Source Technology, Performance Tuning, Tensorflow, Google Cloud, Data Ingestion, Pytorch, Large Language Models, Apache Spark, Containerization, Kubernetes, Machine Learning Operations, Data Pipelines, Docker - **Published:** May 13, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=b808111862e26a41 ## About the Role Design and implement scalable MLOps supportive data pipelines for data ingestion, processing, and storage. Experience deploying models with MLOps tools such as Vertex Pipelines, KubeFlow, or similar platforms. Experience implementing and supporting end-to-end Machine Learning workflows and patterns. Expert level programming skills in Python and experience with Data Science and ML packages and frameworks. Proficiency with containerization technologies (Docker, Kubernetes) and CI/CD practices. Experience working with large-scale machine learning frameworks such as TensorFlow, Caffe2, PyTorch, Spark ML, or related frameworks. Experience and knowledge in the most recent advancements in Gen AI, including Gemini, OpenAI, Claud and exposure to open-source Large Language Models (LLMs). Experience building AI/ML products using technologies such as LLMs, neural networks and others. Experience with RAG and Supervised Tuning techniques. Strong distributed systems skills and knowledge. Development experience of at least one public cloud provider, Preferably Google Cloud Platform. Excellent analytical, written, and verbal communication skills. ## Related Videos - [DevOps for AI: running LLMs in production with Kubernetes and KubeFlow](https://www.wearedevelopers.com/videos/1222-devops-for-ai-running-llms-in-production-with-kubernetes-and-kubeflow) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding) - [Understanding Kubernetes in a visual way](https://www.wearedevelopers.com/videos/100085-understanding-kubernetes-in-a-visual-way) - [Microservices: how to get started with Spring Boot and Kubernetes](https://www.wearedevelopers.com/videos/242-microservices-how-to-get-started-with-spring-boot-and-kubernetes) - [LLMOps-driven fine-tuning, evaluation, and inference with NVIDIA NIM & NeMo Microservices](https://www.wearedevelopers.com/videos/1582-llmops-driven-fine-tuning-evaluation-and-inference-with-nvidia-nim-nemo-microservices) ## 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) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [Everything a Developer Needs to Know About MCP with Neo4j](https://www.wearedevelopers.com/magazine/604-everything-a-developer-needs-to-know-about-mcp-with-neo4j)