E-Solutions

Sr. GCP AI/ML Lead - Vertex AI

โญ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Sr. GCP AI/ML Lead focusing on designing and deploying AI solutions using Vertex AI. Contract length is unspecified, with a pay rate of "unknown." Requires 5+ years in AI/ML, strong Python and SQL skills, and GCP expertise.
๐ŸŒŽ - Country
United States
๐Ÿ’ฑ - Currency
$ USD
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๐Ÿ’ฐ - Day rate
Unknown
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๐Ÿ—“๏ธ - Date
April 1, 2026
๐Ÿ•’ - Duration
Unknown
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๐Ÿ๏ธ - Location
Remote
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๐Ÿ“„ - Contract
Unknown
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๐Ÿ”’ - Security
Unknown
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๐Ÿ“ - Location detailed
United States
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๐Ÿง  - Skills detailed
#NLP (Natural Language Processing) #BigQuery #AI (Artificial Intelligence) #Kubernetes #Deployment #DevOps #Computer Science #PyTorch #Data Engineering #Cloud #Storage #ML (Machine Learning) #GCP (Google Cloud Platform) #Python #Docker #TensorFlow #Data Pipeline #Data Science #Model Deployment #Scala #Langchain #Programming #SQL (Structured Query Language) #Monitoring #Automation #Dataflow
Role description
Role : GCP AI/ML Engineer Location : Remote โ€ข Detailed JD: Responsible for designing, building, and deploying machine learning models and AI-driven systems within the Google Cloud ecosystem. This role bridges data science and software engineering, focusing on creating scalable, production-ready AI solutionsโ€”such as Generative AI, natural language processing, and predictive modelsโ€”using tools like Vertex AI, TensorFlow, and BigQuery. Key Responsibilities o Model Development & Training: Develop and train predictive and generative AI models using Python and frameworks such as TensorFlow, PyTorch, or Scikit-learn, often within Vertex AI. o GCP Implementation: Implement solutions using GCP services like BigQuery, Dataflow, Cloud Functions, and Vertex AI Pipelines to build scalable infrastructure. o MLOps and Automation: Design and automate MLOps pipelines (training, deployment, monitoring) to ensure model performance, scalability, and reliability. o Data Engineering: Construct data pipelines for ingestion, preprocessing, and storage of structured/unstructured data using SQL and BigQuery. o Generative AI Integration: Implement LLMs, retrieval-augmented generation (RAG) patterns, and agentic workflows (e.g., using LangChain). o Optimization & Troubleshooting: Monitor and optimize deployed models for accuracy, latency, and cost-effectiveness. Required Skills and Qualifications o Experience: 5+ years in AI/ML model deployment and software engineering. o Technical Proficiencies: Strong programming skills in Python and SQL. o GCP Expertise: Proven experience with Google Cloud Platform, specifically Vertex AI, Dataflow, and BigQuery. o ML Frameworks: In-depth knowledge of TensorFlow, PyTorch, or Scikit-learn. o DevOps/Containerization: Proficiency with Docker, Kubernetes (GKE), and CI/CD tools. o Education: Bachelorโ€™s or Masterโ€™s degree in Computer Science, AI, Machine Learning, or a related field. Preferred Qualifications o GCP Professional Machine Learning Engineer certification. o Experience with Vertex AI agent builder o Background in Natural Language Processing (NLP) or Computer Vision