Remote Part-Time AI/ML Engineer for Production Systems

erthdev.com; United States; Remote; USD 30,000 - 60,000; Part time

Benefits offered by this job

Paid annual leave

Sick leave

Performance bonuses

Annual salary reviews

Medical insurance

Equipment support

Career growth

Job summary

erthdev.com seeks a part-time AI/ML professional to prototype and implement features for products and internal workflows. You will compare models and approaches, build data pipelines, and connect AI services with backend systems.

You will measure quality, cost, latency, and failure patterns while collaborating with product, security, and backend teams. Flexible hours with strong focus on responsible, measurable impact.

Qualifications

• Practical experience delivering AI/ML features into production-adjacent systems.
• Strong Python skills and understanding of model evaluation and failure analysis.
• Familiarity with large language models, traditional ML, or both.
• Ability to work with APIs and data pipelines alongside backend engineers.
• Clear communication about uncertainty and technical trade-offs.
• Awareness of security and privacy with a product-oriented approach.

Responsibilities

• Prototype and implement AI or ML features for product and internal workflows.
• Compare models, prompts, and approaches against defined success measures.
• Build data preparation and inference pipelines, and connect AI services with backend systems.
• Measure output quality, operating cost, response time, and failure patterns.
• Collaborate with product, backend, and security teams on responsible implementation.
• Document assumptions and evaluation findings, improve monitoring, and protect confidential data.

Skills

Python

Model evaluation

APIs & data pipelines

Communication

Security & privacy

Uncertainty communication

Tools

PyTorch

scikit-learn

vector search

orchestration libraries

cloud ML services

evaluation frameworks

Job description

erthdev.com seeks a part-time AI/ML professional to prototype and implement features for products and internal workflows. You will compare models and approaches, build data pipelines, and connect AI services with backend systems.

You will measure quality, cost, latency, and failure patterns while collaborating with product, security, and backend teams. Flexible hours with strong focus on responsible, measurable impact.