Remote ML Engineer, Vertex AI Platform Builder

Cogleus LLC; Indiana (PA); On-site; USD 83,000 - 138,000; Part time

Benefits offered by this job

Flexible work schedule

Opportunity to shape an AI platform

Collaborative environment

Job summary

Cogleus LLC in the United States is seeking a hands-on ML Engineer with Google Vertex AI expertise to accelerate development of an AI-powered platform. You’ll work with leadership to design, train, and deploy models and to build scalable, production-ready pipelines.

The role is part-time and remote, offering a flexible schedule and the chance to shape an early-stage product. You’ll collaborate with backend engineers and ML ops to ensure performance, monitoring, and reliable model versioning.

Qualifications

• Proven experience with Google Vertex AI (training, deployment, pipelines, model monitoring).
• Strong Python skills and ML frameworks (TensorFlow, PyTorch, scikit-learn).
• Experience in NLP and text classification.
• Familiarity with cloud-based data storage and retrieval (BigQuery, Cloud Storage).
• Solid understanding of ML lifecycle and MLOps best practices.

Responsibilities

• 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.

Skills

NLP experience

Text classification

Python programming

ML lifecycle

MLOps

Tools

TensorFlow

PyTorch

scikit-learn

Google Vertex AI

BigQuery

Cloud Storage

Job description

Cogleus LLC in the United States is seeking a hands-on ML Engineer with Google Vertex AI expertise to accelerate development of an AI-powered platform. You’ll work with leadership to design, train, and deploy models and to build scalable, production-ready pipelines.

The role is part-time and remote, offering a flexible schedule and the chance to shape an early-stage product. You’ll collaborate with backend engineers and ML ops to ensure performance, monitoring, and reliable model versioning.