

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.
๐ - Country
United States
๐ฑ - Currency
$ USD
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๐ฐ - Day rate
Unknown
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๐๏ธ - Date
April 1, 2026
๐ - Duration
Unknown
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๐๏ธ - Location
Remote
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๐ - Contract
Unknown
-
๐ - Security
Unknown
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๐ - Location detailed
United States
-
๐ง - 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
โข 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 solutionsโsuch as Generative AI, natural language processing, and predictive modelsโusing 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: Bachelorโs or Masterโs 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
Role : GCP AI/ML Engineer
Location : Remote
โข 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 solutionsโsuch as Generative AI, natural language processing, and predictive modelsโusing 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: Bachelorโs or Masterโs 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






