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Google- Vertex AI Engineer

1 month ago

Charlotte, United States Ndimensions IT Full time
Job DescriptionJob Description

Location: Charlotte, North Carolina, United States

Day 1 Hybrid Onsite

Job Description:

We are looking for candidates having hands on experience as a Vertex AI Machine Learning Engineer. The Vertex AI Machine Learning Engineer will be responsible for developing, deploying, and managing machine learning models using Google Cloud's Vertex AI platform. The ideal candidate will have a strong background in machine learning, experience with Google Cloud services, and a passion for solving complex problems with AI.

Responsibilities:

  • Design, develop, and deploy machine learning models using Vertex AI.
  • Integrate Vertex AI with other Google Cloud services such as BigQuery, Cloud Storage, and Dataflow.
  • Utilize AutoML capabilities to create high-quality models with minimal manual effort.
  • Develop custom training pipelines for more complex machine learning tasks using frameworks like TensorFlow and PyTorch.
  • Implement and manage Vertex AI Pipelines for orchestrating end-to-end machine learning workflows.
  • Monitor and optimize model performance post-deployment, ensuring models remain accurate and efficient over time.
  • Collaborate with data scientists, software engineers, and other stakeholders to understand business requirements and translate them into effective AI solutions.
  • Perform hyperparameter tuning to enhance model performance.
  • Utilize Vertex AI Feature Store for feature management and reuse.
  • Conduct online and batch predictions using Vertex AI prediction services.
  • Adhere to MLOps best practices for model versioning, deployment, and lifecycle management.

Requirements:

  • Proven experience with machine learning frameworks such as TensorFlow, PyTorch, and scikit-learn.
  • Hands-on experience with Google Cloud Platform (GCP) services, specifically Vertex AI.
  • Strong programming skills in Python or a similar language.
  • Familiarity with data processing tools like Apache Beam, Dataflow, or similar.
  • Understanding of machine learning algorithms and techniques, including supervised and unsupervised learning, deep learning, and reinforcement learning.
  • Experience with AutoML tools and techniques.
  • Excellent problem-solving skills and the ability to work in a fast-paced environment.
  • Strong communication and collaboration skills.

Preferred Qualifications:

  • Google Cloud Professional Machine Learning Engineer certification.
  • Experience with MLOps tools and practices.
  • Familiarity with Kubernetes and Docker for containerization and orchestration.
  • Knowledge of big data technologies like Big Query, Spark, and Hadoop.