Job Description

At Peoplebox.ai, we are revolutionizing the talent space by leveraging AI to automate how companies hire, develop and retain top performers. Peoplebox AI platform uses talent management insights to fully automate candidate screening (both inbound and existing one in ATS) and identify the best fits instantly.

It also enriches candidates resume by leveraging public information like LinkedIn, Crunchbase, Github and media coverage and provides their strengths and weaknesses to make more informed hiring decisions with unparalleled speed and accuracy.

We’re looking for a Lead AI Engineer to help us build and scale our AI talent solutions and take them to the next level.

Job Description
As a Lead AI Engineer at Peoplebox.ai, you will drive the design, development, and deployment of AI-driven products that are transforming how companies manage talent acquisition and management. You will work closely with cross-functional teams to deliver cutting-edge machine learning solutions that enhance our talent intelligence platform. We are particularly focused on Natural Language Processing (NLP) applications and require someone with deep expertise in LLMs and Machine learning models

Key Responsibilities

• AI Product Development: Design, build, and scale AI/ML solutions, specifically in the NLP space, to production.
• NLP & LLM Expertise: Lead the development and fine-tuning of NLP models and LLMs to enhance the screening and matching processes.
• Data Pipeline: Build and maintain robust data pipelines that enable real-time processing of structured and unstructured data (resumes, social profiles, public data).
• Collaboration: Work with product managers, data scientists, and software engineers to integrate AI/ML solutions with the platform’s backend.
• Performance Optimization: Ensure scalability, efficiency, and accuracy of AI algorithms and models in production environments.

Required Qualifications

• Experience: 4+ years of backend development experience, with at least 2+ years focused on building, deploying, and scaling AI/ML products in production environments.
• NLP & LLM: Strong experience in specifically with NLP applications and LLMs (such as GPT, BERT, etc.), including model training, fine-tuning, and deploying at scale.
• Programming: Proficient in Python, TensorFlow, PyTorch, and other relevant AI/ML libraries and frameworks.
• Machine Learning: Deep understanding of machine learning techniques, including supervised and unsupervised learning, classification, regression, and clustering.
• Data Engineering: Experience building data pipelines for both structured and unstructured data processing.
• Cloud: Hands-on experience with cloud services (AWS, GCP, or Azure) for AI/ML deployment.

If you’re passionate about AI, machine learning, and building scalable products, we’d love to hear from you! Join us in disrupting how companies hire, develop and retain top talent.