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AI Engineer
Ref Id: HREZ-10251
Published Date: Apr 9, 2026
Job location: California, United States
Work arrangement: Hybrid
Job ID: 4090506
Employment type: Full-time
General information
Ref Id: HREZ-10251
Published Date: Apr 9, 2026
Job location: California, United States
Work arrangement: Hybrid
Job ID: 4090506
Employment type: Full-time
Description

AI Engineer — hireEZ

Location: California (Hybrid or Remote – U.S.)
Department: Engineering / AI
Employment Type: Full-Time

About hireEZ

hireEZ is an AI-first talent acquisition platform helping organizations transform recruiting through intelligent sourcing, engagement automation, and agentic AI workflows. Our platform combines data intelligence, automation, and generative AI to enable recruiters to identify, engage, and hire top talent faster.
We are building next-generation AI systems that redefine how companies discover and connect with talent globally.

Role Overview

We are seeking an innovative AI Engineer to design, build, and deploy scalable AI systems powering hireEZ’s intelligent recruiting platform.
You will work at the intersection of LLMs, machine learning, data engineering, and product development, transforming advanced AI research into production-ready features used by thousands of recruiters worldwide.
This role requires strong engineering fundamentals combined with practical experience deploying AI models into real-world SaaS environments.

Key Responsibilities

  • Design, develop, and deploy AI/ML models supporting sourcing, matching, ranking, and candidate engagement workflows
  • Build and optimize LLM-powered features, including AI agents, semantic search, RAG pipelines, and conversational assistants
  • Develop scalable MLOps pipelines for model training, evaluation, deployment, and monitoring
  • Collaborate with product managers, software engineers, and data teams to translate business needs into AI solutions
  • Improve model performance, accuracy, latency, and cost efficiency
  • Implement responsible AI practices including bias mitigation, privacy protection, and model explainability
  • Integrate AI services with cloud infrastructure and production APIs
  • Stay current with advancements in Generative AI, agentic workflows, and applied machine learning
Typical AI engineering roles involve designing models, managing lifecycle deployment, and collaborating cross-functionally to move AI systems from prototype to production.

Required Qualifications

  • Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or related field
  • 3+ years of experience in AI/ML engineering or applied machine learning
  • Strong programming skills in Python
  • Experience with:
    • Large Language Models (OpenAI, Llama, Claude, etc.)
    • NLP, semantic search, or recommendation systems
    • ML frameworks (PyTorch, TensorFlow, Scikit-learn)
  • Experience building production AI systems or APIs
  • Familiarity with cloud platforms (AWS, GCP, or Azure)
  • Strong understanding of data pipelines and model evaluation

Preferred Qualifications

  • Experience building AI agents or autonomous workflows
  • Knowledge of RAG architectures and vector databases
  • SaaS or recruiting technology experience
  • Experience with distributed systems and microservices
  • Familiarity with prompt engineering and AI safety techniques

Compensation & Benefits

  • Salary Range (California): $140,000 – $210,000 USD
    (Actual compensation depends on experience, skills, and location.)
  • Equity participation
  • Comprehensive health, dental, and vision insurance
  • Flexible PTO and remote work options
  • Learning & development budget
  • Opportunity to work on cutting-edge AI shaping the future of recruiting
AI engineer roles commonly fall within six-figure compensation ranges due to specialized ML and LLM expertise.

Why Join hireEZ

  • Build real-world AI products used daily by global recruiting teams
  • Work on agentic AI systems, not just experimentation
  • High ownership, fast product iteration, and startup innovation culture
  • Direct impact on the future of talent acquisition technology


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