AI Developer

Job Summary Key Responsibilities

• Design and develop the core AI engine for Kyra with context-aware, multi-turn conversations covering nutrition, exercise, supplements, sleep, stress, and overall wellness.
• Build a food recognition pipeline using computer vision models such as YOLO , EfficientNet , or custom CNNs to identify food items and estimate nutritional values.
• Develop a medical and lab report analysis module using OCR technologies like Tesseract and PaddleOCR , combined with NLP for extracting biomarkers and generating health insights.
• Create a personalized recommendation engine for workout plans, diet suggestions, wellness challenges, and habit tracking based on user goals and historical data.
• Fine-tune and deploy Large Language Models (LLMs) using Python , PyTorch , TensorFlow , and Hugging Face Transformers .
• Develop Retrieval-Augmented Generation (RAG) pipelines using vector databases such as Pinecone , Weaviate , or ChromaDB .
• Build a real-time 3D avatar speech and lip-sync pipeline by integrating Text-to-Speech engines, phoneme extraction, and viseme mapping.
• Implement voice interaction using Speech-to-Text technologies like Whisper , natural language understanding, and conversational AI workflows.
• Design prompt engineering frameworks, AI guardrails, and safety filters to ensure medically responsible responses.
• Develop evaluation frameworks to measure model accuracy, response quality, hallucination rates, and user satisfaction.
• Optimize inference performance through model quantization, batching, caching, and GPU/CPU resource management.
• Collaborate closely with backend, frontend, and 3D development teams to integrate AI services into the product.

Requirements & Qualifications

• 2-4 years of experience in AI/ML development with expertise in NLP, Computer Vision, or Conversational AI.
• Strong Python programming skills with extensive experience using PyTorch or TensorFlow .
• Hands-on experience fine-tuning Large Language Models such as GPT, LLaMA, Mistral, or similar foundation models.
• Experience designing and deploying Retrieval-Augmented Generation (RAG) architectures and vector databases.
• Strong understanding of computer vision techniques including image classification, object detection, and OCR.
• Experience with speech technologies including Text-to-Speech (ElevenLabs, Coqui, Azure TTS), Whisper, and audio processing.
• Knowledge of 3D avatar animation pipelines, lip-sync technologies, viseme mapping, and blend shapes.
• Experience with LangChain, LlamaIndex, or similar LLM orchestration frameworks.
• Strong understanding of prompt engineering, structured output generation, and AI safety practices.
• Experience deploying machine learning models using FastAPI, model versioning, monitoring, and A/B testing.
• Familiarity with cloud-based ML services such as AWS SageMaker, Google Vertex AI, or Azure Machine Learning.

Tools Technologies

• Python
• PyTorch
• TensorFlow
• Hugging Face Transformers
• LangChain
• LlamaIndex
• OpenAI API
• Pinecone
• ChromaDB
• Weaviate
• YOLO
• EfficientNet
• Tesseract OCR
• PaddleOCR
• Whisper
• ElevenLabs
• Coqui TTS
• FastAPI
• Docker
• AWS SageMaker
• Weights Biases
• MLflow
• Jupyter Notebook
• Git

Nice to Have

• Experience developing AI solutions for health-tech or wellness platforms.
• Knowledge of healthcare interoperability standards such as FHIR and HL7.
• Experience with Reinforcement Learning from Human Feedback (RLHF).
• Familiarity with Unity or Unreal Engine for integrating AI-driven 3D avatars.
• Published research papers or open-source contributions in NLP, Computer Vision, or Generative AI.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.