Ai Engineer Google Cloud Google Cloud Platform

  • Posted 1 hour ago | Updated 1 hour ago

Overview

Remote
$80,000 - $140,000
Accepts corp to corp applications
Contract - W2
Contract - Independent
Contract - 36 Month(s)
Able to Provide Sponsorship

Skills

Algorithms
Amazon Web Services
Artificial Intelligence
Cloud Computing
Cloud Storage
Computer Vision
Continuous Delivery
Continuous Integration
Data Flow
Data Processing
Deep Learning
Docker
Evaluation
Generative Artificial Intelligence (AI)
Good Clinical Practice
Google Cloud
Google Cloud Platform
Kubernetes
Machine Learning (ML)
Machine Learning Operations (ML Ops)
Microservices
Microsoft Azure
Natural Language Processing
PyTorch
Python
Real-time
Regulatory Compliance
SQL
Scalability
Streaming
TensorFlow
Terraform
Training
Vertex
scikit-learn

Job Details

We are seeking a highly skilled AI Engineer with strong experience in cloud-based AI/ML solutions, preferably on Google Cloud Platform (Google Cloud Platform). The ideal candidate will design, build, deploy, and scale machine learning and AI systems in a production cloud environment.

Key Responsibilities

  • Design, develop, and deploy AI/ML models in cloud environments (Google Cloud Platform preferred; AWS/Azure acceptable)

  • Build end-to-end ML pipelines including data ingestion, feature engineering, training, evaluation, and deployment

  • Implement MLOps practices using CI/CD, monitoring, versioning, and model lifecycle management

  • Work with large datasets using cloud-native data services

  • Optimize model performance, scalability, and cost in cloud environments

  • Collaborate with data engineers, product teams, and stakeholders to translate business needs into AI solutions

  • Ensure security, compliance, and best practices in cloud AI implementations

Required Skills

  • Strong experience as an AI Engineer / ML Engineer

  • Hands-on experience with Google Cloud Platform (Vertex AI, BigQuery, Cloud Storage, Dataflow, Pub/Sub)

  • Proficiency in Python and ML libraries (TensorFlow, PyTorch, Scikit-learn)

  • Experience with REST APIs, microservices, and containerization (Docker, Kubernetes)

  • Solid understanding of ML algorithms, deep learning, and model evaluation

  • Experience with SQL and data processing frameworks

Good to Have

  • Experience with AWS or Azure in addition to Google Cloud Platform

  • Knowledge of LLMs, GenAI, NLP, or Computer Vision use cases

  • Experience with Terraform / Infrastructure as Code

  • Exposure to real-time or streaming ML systems

Please Do Not Submit

  • Pure Data Scientists with no production deployment experience

  • Candidates without cloud AI/ML implementation experience

Submission Requirements

Please ensure resumes clearly highlight:

  • Google Cloud Platform AI/ML project experience

  • Model deployment and MLOps responsibilities

  • End-to-end ownership of AI solutions

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

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