AI engineer lead

About the role:

We are developing a next-generation Virtual AI Interviewer capable of conducting real-time interviews, generating context-aware questions, analyzing voice/video responses, and providing candidate assessments automatically. We’re looking for an AI Engineer with 2-3 years of experience and a strong foundation in Natural Language Processing, Generative AI, and conversational systems to build and scale this product from the ground up.

Responsibilities:

• Design and develop AI models for automated question generation, evaluation, and response understanding.
• Build conversational logic and dialogue systems that simulate realistic, human-like interviews.
• Implement NLP and speech recognition systems for candidate interaction through text and voice.
• Integrate behavioral and emotional analysis modules for tone, sentiment, and body-language detection (using vision models).
• Collaborate with backend and frontend teams to integrate AI models into live interview workflows.
• Develop and optimize model pipelines using frameworks like PyTorch, TensorFlow, or Hugging Face.
• Continuously improve model accuracy, contextual understanding, and question relevance.
• Stay updated with the latest advancements in LLMs, multimodal models, and AI ethics.

Required expertise:

• Bachelor’s or Master’s degree in Computer Science, AI, Data Science, or related field.
• 2–3 years of experience in building NLP, CV, or speech-based AI applications.
• Proficiency in Python, PyTorch/TensorFlow, and Transformers (Hugging Face).
• Strong understanding of LLMs, RAG systems, embeddings, and prompt engineering.
• Experience with OpenAI, Anthropic, or custom fine-tuning APIs.
• Familiarity with Speech-to-Text (Whisper, DeepSpeech) and Text-to-Speech (TTS) frameworks.
• Working knowledge of emotion/sentiment analysis, face detection, or pose estimation (OpenCV, Mediapipe).
• Good understanding of backend integration (FastAPI, Flask, or Node.js).
• Strong analytical, problem-solving, and communication skills.

Good to have:

• Experience with LangChain, RAG pipelines, or vector databases (Pinecone, FAISS, Chroma).
• Exposure to real-time video/audio streaming applications.
• Background in human-computer interaction, psychometric scoring, or recruitment tech.
• Understanding of cloud deployment (AWS, GCP, Azure) and Docker/Kubernetes.

What you will build:

• Conduct live interviews using voice/video.
• Auto-generate domain-specific questions.
• Assess candidate confidence, tone, and relevance.
• Deliver detailed post-interview analysis reports.