About the RoleWe are looking for a full-time MLOps Engineer to join our team remotely. This role involves building and optimizing AI/ML infrastructure at scale. You will be responsible for deploying, maintaining, and scaling machine learning models while working with cloud-native architectures.Location: RemoteType: Paid Full-time, PermanentExperience: 1+ years in MLOps, LLMOps, or a related fieldKey ResponsibilitiesDesign, develop, and deploy scalable MLOps/LLMOps pipelines.Work with FastAPI, Celery, Redis, and Kafka for backend and distributed processing.Implement Retrieval-Augmented Generation (RAG) workflows and optimize LLM deployment.Deploy models using AWS (Lambda, API Gateway, S3, EKS, Athena, Glue, etc.).Manage infrastructure with Docker, Kubernetes, Terraform, and CI/CD pipelines (GitHub Actions, ArgoCD).Monitor and improve system performance using Prometheus, Grafana, Loki, or AWS CloudWatch.Integrate vector databases (Milvus, Pinecone) for embedding storage.Develop agentic/self-reflective Large Language Model (LLM) applications.Requirements1+ years of experience in MLOps/LLMOps with cloud deployments.Proficiency in Python, FastAPI, and distributed systems.Experience with message queues (RabbitMQ, Kafka) and caching (Redis).Hands-on experience in deploying at least one scalable AI/ML project in the cloud.Strong understanding of DevOps, CI/CD pipelines, Kubernetes, and Terraform.Experience working with LLMs, Hugging Face, LangChain, or LlamaIndex.Strong portfolio showcasing real-world implementations.Nice to HaveContributions to open-source projects related to backend, AI, or ML.Experience with serverless computing (AWS Lambda, API Gateway).What We OfferA chance to work on cutting-edge AI/ML projects.A fast-paced, flexible, and innovation-driven work environment.Direct mentorship and growth opportunities in MLOps and AI engineering.
Job Title
MLOps Engineer (Full-Time)