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Machine Learning Engineer – Google Vertex AI Specialist Remote; US , global

Remote / Online - Candidates ideally in
Noblesville, Hamilton County, Indiana, 46060, USA
Listing for: Cogleus LLC
Full Time, Part Time, Contract, Remote/Work from Home position
Listed on 2026-10-30
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 83000 - 131000 USD Yearly USD 83000.00 131000.00 YEAR
Job Description & How to Apply Below
Position: Machine Learning Engineer – Google Vertex AI Specialist | Location: Remote (US preferred, but open to global

Job Description:

Part Time, Remote

USA

Posted 1 year ago

Job Description:

We are currently developing an AI-powered platform that will leverage machine learning to deliver advanced automation and decision-making capabilities in a targeted domain. We’re seeking a hands-on ML Engineer with Google Vertex AI expertise to help us accelerate development and bring innovative capabilities to market. You’ll work directly with our leadership and project team to design, develop, and deploy machine learning models on Google Vertex AI, integrating them into a scalable, production-ready environment.

Your work will drive model performance, platform intelligence, and operational efficiency.

Here Are Some Things You’ll Be Working On:
  • Design, build, and deploy ML models on Google Vertex AI for NLP and classification tasks.
  • Develop data ingestion, transformation, and storage workflows.
  • Train, evaluate, and optimize models for performance and accuracy.
  • Collaborate with backend developers to integrate ML components into the platform.
  • Implement monitoring, retraining, and model versioning processes.
  • Contribute to architecture decisions for scalability and maintainability.
Required Qualifications
  • Proven experience with Google Vertex AI (training, deployment, pipelines, model monitoring).
  • Strong Python skills and experience with ML frameworks (Tensor Flow, PyTorch, scikit-learn, etc.).
  • Experience in NLP and text classification.
  • Familiarity with cloud-based data storage and retrieval (Big Query, Cloud Storage).
  • Strong understanding of ML lifecycle and MLOps best practices.
Nice-to-Haves
  • Experience with Google Cloud integrations (Big Query ML, AI Platform).
  • Knowledge of domain-specific AI applications in business operations.
  • Prior startup or MVP experience.
What We Offer
  • Flexible work schedule.
  • Opportunity to shape an AI platform from the ground up.
  • Collaborative, fast-moving, and outcome-driven environment.
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