Google Cloud Platform

7 days ago


India People Prime Worldwide Full time

About the Company Our client is a trusted global innovator of IT and business services, present in 50+ countries. They specialize in digital & IT modernization, consulting, managed services, and industry-specific solutions. With a commitment to long-term success, they empower clients and society to move confidently into the digital future. Job Description Important Note (Please Read Before Applying) 🚫 Do NOT apply if: You have less than 5 years in GCP. You do not have hands-on PyTorch,TensorFlow. You are on a notice period longer than 15 days. Apply ONLY if you meet ALL criteria above. Random / irrelevant applications will not be processed. Job Title: Google Cloud Platform Location: Remote (Global) | Preferred: US / EU Time Zones Job Type: Full-Time Experience Required: 8+ Years About the Role: We're looking for a Senior ML Inference Engineer with deep expertise in containerized ML workflows, large model inference, and cloud-native deployment. You'll work at the intersection of MLOps, deep learning, and cloud infrastructure, helping productionize some of the most powerful language models available today. Key Responsibilities: - Deploy and optimize large-scale models (e.g., Mixtral, Gemma) for inference performance and latency. - Build and maintain highly optimized Docker containers, using multi-stage builds and best practices for performance and security. - Work with high-performance inference servers such as vLLM for efficient GPU utilization in production. - Manage and automate deployment on Google Cloud Platform (GCP) using tools like GKE, Cloud Run, and Artifact Registry. - Support model deployment pipelines for Google Cloud's Model Garden, handling complex dependency resolution. - Write and maintain clear, reproducible documentation for container builds, deployment processes, and system management. 💼 Requirements: - 8+ years of experience in software/ML engineering roles. - Advanced knowledge of PyTorch and TensorFlow. - Strong hands-on experience with Docker and container-based deployment workflows. - Proven experience with ML inference optimization, especially in GPU-accelerated environments. - Familiarity with LLMs and open-weight models (e.g., Mixtral, Gemma, LLaMA, Falcon). - Solid grasp of Google Cloud services for container orchestration. - Excellent communication skills and a passion for clean, scalable infrastructure. 🏷️ Nice to Have: - Experience with other inference frameworks (e.g., TensorRT, ONNX Runtime, DeepSpeed). - Familiarity with CI/CD pipelines and infrastructure as code.



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