AI/ML Engineer

TL;DR

AI/ML Engineer: Develop, train, and deploy machine learning models across our infrastructure for fraud detection, support automation, and content generation, including UltaBuilder AI. Focus on designing scalable models, improving LLM integration, and ensuring security and bias control.

Location: Remote work flexibility

Company

hirify.global is investing heavily in AI-powered hosting innovation.

What you will do

• Design, train, and optimize machine learning models for fraud detection, support automation, and user behavior analytics.
• Collaborate on building UltaBuilder AI, generating website content, layout, and structure from user prompts.
• Deploy models using scalable architectures, APIs, and GPU/CPU clusters.
• Clean, label, and process large datasets collected from user interactions and system logs.
• Implement continuous training and evaluation loops for production-grade models.
• Work with AI Prompt Engineers and Product Managers to improve LLM integration and hybrid pipelines.

Requirements

• 3+ years of experience in Machine Learning or Data Science.
• Proficiency in Python, TensorFlow, PyTorch, or other ML frameworks.
• Strong understanding of supervised, unsupervised, and reinforcement learning.
• Experience building and deploying models via REST APIs or microservices.
• Familiarity with data labeling tools, model tuning, and vector embeddings.
• Experience working with large datasets and cloud infrastructure (AWS, GCP, or self-hosted clusters).

Nice to have

• Experience working with LLMs like OpenAI, Mistral, Claude, or open-source models.
• Knowledge of fraud detection logic in SaaS, hosting, or fintech.
• Experience with NLP tasks: classification, summarization, or embedding generation.
• Familiarity with vector databases, prompt engineering, or retrieval-augmented generation (RAG).
• Previous work with AI-driven website builders, chatbots, or smart support agents.

Culture & Benefits

• Competitive salary and performance-based bonuses.
• Equity or token options based on project impact.
• Remote work flexibility.
• Access to cutting-edge infrastructure, compute resources, and GPU training environments.
• Opportunity to build AI systems used by thousands of global customers daily.