Google Cloud LLM & MLOps Expert

  • Alpharetta, GA
  • Posted 1 day ago | Updated 15 hours ago

Overview

Remote
On Site
Hybrid
$60 - $90
Contract - W2
Contract - Independent
Contract - 36 Month(s)
Able to Provide Sponsorship

Skills

Algorithms
Amazon SageMaker
Artificial Intelligence
Cloud Computing
Cloud Storage
Continuous Delivery
Continuous Integration
Data Flow
Data Science
DevOps
Generative Artificial Intelligence (AI)
Good Clinical Practice
Google Cloud
Google Cloud Platform
Kubernetes
Large Language Models (LLMs)
Lifecycle Management
Machine Learning (ML)
Machine Learning Operations (ML Ops)
Management
Microsoft Azure
Prompt Engineering
PyTorch
Python
Regulatory Compliance
Research Design
SQL
TensorFlow
Terraform
Use Cases
Vertex
scikit-learn
Collaboration
Conflict Resolution
Data Governance
Docker
Evaluation
Innovation
JAX
Mentorship
Problem Solving
Scalability
Training
Workflow

Job Details

All positions require 10+ years of experience with domain expertise. Junior candidates may share their resumes for future opportunities, while experienced professionals who match the requirements will receive an immediate response on email.

 

We are seeking a highly experienced LLM (Large Language Model) and MLOps Expert with a strong background in Google Cloud Platform (Google Cloud Platform) to design, deploy, and optimize enterprise-scale AI/ML solutions. The ideal candidate will have deep expertise in AI/ML, cloud-native architectures, and operationalizing machine learning workflows in production.

Key Responsibilities

  • Design and implement MLOps pipelines on Google Cloud Platform (Vertex AI, AI Platform, Kubeflow, CI/CD).

  • Deploy, fine-tune, and manage Large Language Models (LLMs) for real-world business use cases.

  • Automate ML lifecycle processes including data ingestion, training, evaluation, and deployment.

  • Ensure scalability, reliability, and security of ML workloads in cloud environments.

  • Collaborate with Data Scientists, ML Engineers, and Cloud Architects to deliver enterprise AI solutions.

  • Implement monitoring, logging, and governance for deployed ML models.

  • Optimize cloud resources and cost for high-performance ML workloads.

Required Qualifications

  • 10+ years of experience in Data Science, Machine Learning, or Cloud Engineering.

  • Strong expertise in Google Cloud Platform (Google Cloud Platform) – Vertex AI, BigQuery, Cloud Storage, GKE, Pub/Sub.

  • Hands-on experience with MLOps frameworks (Kubeflow, MLflow, TFX).

  • Proven track record in training and fine-tuning LLMs (OpenAI, Hugging Face, PaLM, etc.).

  • Proficiency in Python, TensorFlow, PyTorch, or JAX.

  • Solid understanding of CI/CD, DevOps, and containerization (Docker, Kubernetes).

  • Excellent problem-solving skills and ability to work in fast-paced environments.

Preferred Skills

  • Experience with multi-cloud or hybrid AI solutions.

  • Knowledge of data governance, security, and compliance in AI.

  • Prior experience mentoring or leading AI/ML engineering teams.

Why Join Us?

  • Opportunity to work on cutting-edge AI/ML and LLM projects at scale.

  • Collaborative and innovation-driven culture.

  • Competitive compensation and growth opportunities.

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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