Role Overview:
This role focuses on developing and refining an AI-powered recruitment tool named Zara to automate candidate sourcing, screening, and engagement processes. The position requires deep technical expertise in machine learning and AI systems while collaborating with cross-functional teams to deploy scalable solutions.
Key Responsibilities:
• Design, implement, and optimize machine learning models to improve Zara’s candidate matching accuracy and efficiency.
• 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 metrics.
• Ensure compliance with privacy regulations and ethical AI standards in recruitment workflows.
Required Skills & Qualifications:
• 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.
More About the Opportunity:
This role offers a unique opportunity to work on a cutting-edge AI recruiter system used by organizations worldwide. The position contributes to reducing hiring bias and improving talent acquisition efficiency through technology.
Equal Opportunity Employer:
We hire based on skills and expertise. All qualified candidates are welcome regardless of background, experience, or prior employment history. Applications are reviewed solely on demonstrated technical ability and qualifications.
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