[Remote] MLOps / LLM Engineer (Google Cloud Platform & Vertex AI)

Note: The job is a remote job and is open to candidates in USA. Dice is the leading career destination for tech experts at every stage of their careers. Our client, Hexacorp, is seeking an MLOps / LLM Engineer with expertise in Google Cloud Platform and Vertex AI to design, deploy, and manage large-scale AI/ML solutions. The role involves building MLOps pipelines, optimizing large language models, and ensuring the production-grade deployment of advanced AI solutions. Responsibilities • Build and manage MLOps pipelines for training, evaluation, deployment, and monitoring of ML/LLM models using Vertex AI Pipelines. • Deploy, fine-tune, and optimize LLMs (PaLM, Gemini, BERT, Llama, GPT-based models) on Vertex AI / GKE. • Automate infrastructure provisioning using Terraform / Deployment Manager. • Implement CI/CD pipelines with Google Cloud Platform tools (Cloud Build, Artifact Registry, GitOps/ArgoCD). • Develop and manage feature stores, model registries, and monitoring solutions. • Optimize cost and performance for AI/ML workloads on Google Cloud Platform. • Implement observability (logging, monitoring, and alerting) for ML/LLM production systems. • Collaborate with Data Scientists, ML Engineers, and Cloud Architects to integrate AI solutions into enterprise systems. • Ensure security, governance, and compliance for LLM/AI workloads. Skills • 7+ years of experience in DevOps/MLOps/Cloud Engineering. • Hands-on expertise with Google Cloud Platform (IAM, VPC, GKE, BigQuery, Dataflow, Pub/Sub). • Strong experience with Vertex AI (training, endpoints, pipelines, feature store). • Proven experience with LLMs: fine-tuning, prompt engineering, serving APIs, and optimizing performance. • Proficiency in Python and ML frameworks (TensorFlow, PyTorch, Hugging Face, LangChain). • Strong knowledge of CI/CD pipelines and automation tools. • Experience with Kubernetes (GKE), Docker, Helm. • Knowledge of monitoring & observability tools (Prometheus, Grafana, Stackdriver). • Google Professional ML Engineer or Cloud Architect certification. • Prior experience with LangChain, RAG (Retrieval Augmented Generation), vector databases (Pinecone, FAISS, Vertex Matching Engine). • Experience in deploying GenAI applications on Google Cloud Platform. • Understanding of MLOps frameworks (Kubeflow, MLflow, TFX). Company Overview • Welcome to Jobs via Dice, the go-to destination for discovering the tech jobs you want. It was founded in undefined, and is headquartered in , with a workforce of 0-1 employees. Its website is Apply tot his job