Overview
Skills
Job Details
We are looking for a Large Language Model (LLM) Engineer with strong expertise in Google Cloud Platform (Google Cloud Platform), Vertex AI, and Generative AI frameworks. This role involves building, fine-tuning, and deploying LLM-based solutions for real-world enterprise use cases, leveraging the latest in Generative AI and MLOps practices.
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Design and implement LLM-powered applications using Vertex AI, PaLM, and Generative AI Studio.
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Fine-tune foundation models for NLP, chatbots, summarization, semantic search, and RAG (Retrieval-Augmented Generation).
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Build scalable end-to-end ML pipelines with Vertex AI Pipelines / Kubeflow.
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Deploy and monitor LLM APIs & custom models on Google Cloud Platform (Cloud Run, GKE, Cloud Functions).
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Integrate enterprise data sources with LLMs using BigQuery, Vector Databases, and Embedding Models.
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Implement evaluation metrics, prompt engineering, and responsible AI practices.
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Work with DevOps teams to ensure CI/CD, observability, and cost optimization for AI workloads.
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Hands-on expertise in Google Cloud Platform AI stack: Vertex AI, BigQuery ML, Generative AI Studio, PaLM API.
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Strong background in LLM frameworks: LangChain, Hugging Face, OpenAI API, Transformers.
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Proficiency in Python, REST APIs, FastAPI/Flask for building AI services.
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Knowledge of Vector Databases (Pinecone, Weaviate, FAISS, Chroma).
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Experience in ML pipelines, MLOps, and model monitoring on Google Cloud Platform.
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Solid understanding of NLP techniques, embeddings, and fine-tuning strategies.
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Familiarity with Kubernetes, Docker, Terraform, GitOps.
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Google Cloud Platform Certifications: Professional Machine Learning Engineer / Data Engineer.
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Experience with multi-modal LLMs (text, image, speech).
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Exposure to Responsible AI & data governance practices.
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Prior work in productionizing Generative AI applications at scale.
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Work on cutting-edge LLM & Generative AI projects.
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Collaborate with AI/ML experts solving enterprise challenges.
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Opportunity to grow into AI Solutions Architect / GenAI Lead.