This role focuses on developing and refining an AI-powered recruitment tool named Zara to automate candidate sourcing, screening, and engagement processes, requiring deep technical expertise in machine learning and AI systems while collaborating with cross-functional teams to deploy scalable solutions.
About the Role — Engineering Zara’s AI Recruitment System
Product: Zara, an AI-powered recruitment automation tool
Core Function: Automating candidate sourcing, screening, and engagement
Technical Scope: Machine learning models, NLP infrastructure, and API integrations
Compensation: $160K – $300K/yr
Work Format: Fully remote, work from anywhere
Career Impact & AI Engineering Opportunity
Total Flexibility: Fully remote role, work from anywhere globally
Technical Ownership: Design, implement, and optimize ML models improving candidate matching accuracy
Global Impact: Work on a cutting-edge AI recruiter system used by organizations worldwide
Mission-Driven Work: Contribute to reducing hiring bias and improving talent acquisition efficiency
 Position Overview
This position requires deep technical expertise in machine learning and AI systems while collaborating with cross-functional teams to deploy scalable solutions. The role centers on designing, implementing, and optimizing machine learning models to improve Zara’s candidate matching accuracy and efficiency, alongside developing backend infrastructure for natural language processing.
 Why This Role Matters: As the engineer behind Zara, you design, implement, and optimize machine learning models that directly improve candidate matching accuracy across a global AI recruitment platform, develop and maintain backend infrastructure supporting natural language processing for resume parsing and job description analysis, integrate Zara with applicant tracking systems, HR databases, and third-party job platforms via APIs, collaborate with data scientists and product teams to refine AI training datasets and evaluate model performance, ensure compliance with privacy regulations and ethical AI standards in recruitment workflows, and contribute to reducing hiring bias and improving talent acquisition efficiency for organizations worldwide.
Key Responsibilities
ML Model Development
- Design, implement, and optimize machine learning models to improve Zara’s candidate matching accuracy and efficiency
NLP & Backend Infrastructure
- Develop and maintain backend infrastructure supporting natural language processing for resume parsing and job description analysis
Systems Integration
- Integrate Zara with applicant tracking systems, HR databases, and third-party job platforms via APIs
Collaboration & Compliance
- Collaborate with data scientists and product teams to refine AI training datasets and evaluate model performance metrics
- Ensure compliance with privacy regulations and ethical AI standards in recruitment workflows
Qualifications & Requirements
Essential Skills
- Proficiency in Python, including experience with machine learning frameworks like TensorFlow or PyTorch
- Strong background in natural language processing, including experience with libraries such as spaCy or Hugging Face
- Experience building and deploying scalable AI systems in production environments
- Familiarity with cloud platforms (AWS, GCP, or Azure) and containerization tools like Docker
- Knowledge of SQL and NoSQL databases for data extraction and integration
- Understanding of ethical AI principles and bias mitigation techniques in recruitment systems
- Experience with RESTful APIs and microservices architecture
- Background in data pipeline development and ETL processes
About the Opportunity
This role offers a unique opportunity to work on a cutting-edge AI recruiter system used by organizations worldwide, contributing to reducing hiring bias and improving talent acquisition efficiency through technology. Despite its “Technical Recruiter” title, the position is fundamentally an AI/ML engineering role focused on building and refining the technology behind automated recruitment. All qualified candidates are welcome regardless of background, experience, or prior employment history, with applications reviewed solely on demonstrated technical ability and qualifications.
Career Consideration: This role suits hands-on ML/AI engineers building recruitment technology, not candidates with a traditional human-recruiting background — review the required technical stack carefully before applying.
 Who Should Apply?
- Machine Learning Engineers:Â With proven Python, TensorFlow, or PyTorch experience
- NLP Specialists:Â Experienced with spaCy, Hugging Face, or similar libraries
- AI Systems Engineers:Â Comfortable deploying scalable AI systems in production
- Cloud & DevOps-Familiar Developers:Â Skilled with AWS, GCP, Azure, and Docker
- Ethical AI Practitioners:Â Interested in bias mitigation within recruitment technology
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