Overview

Description

Responsibilities:
  • Design and implement end-to-end NLP solutions, specifically focusing on RAG architectures to power internal knowledge bases and customer-facing chatbots
  • Develop and fine-tune models for Automatic Speech Recognition (ASR/STT) to transcribe live betting calls and Speech-to-Text applications for customer support analysis
  • Build models to classify user intent, detect toxic behavior, and analyze sentiment to support Responsible Gambling initiatives
  • Experiment with and optimize Large Language Models (LLMs) using techniques like quantization, fine-tuning (PEFT/LoRA), and prompt engineering to align with business logic
  • Write robust, production-ready Python code, ensuring modularity and scalability within a microservices architecture
  • Manage the lifecycle of NLP models, including containerization (Docker), orchestration (Kubernetes), and monitoring drift in production environments
  • Work closely with backend engineers and product managers to integrate AI features into existing betting platforms and CRM tools
Required Qualifications:
  • 3+ years in AI/ML engineering with a dedicated focus on NLP tasks
  • Expert-level Python skills; strong familiarity with frameworks like PyTorch, TensorFlow, or JAX
  • Hands-on experience with LLM frameworks (LangChain, LlamaIndex), Vector Databases (Pinecone, Milvus, or Weaviate), and Hugging Face transformers
  • Experience with speech toolkits such as OpenAI Whisper, Kaldi, or similar ASR technologies
  • Experience with CI/CD pipelines, API development (FastAPI/Flask), and model serving (Triton, TorchServe)
  • Ability to translate complex gambling compliance and user experience requirements into technical AI solutions
Note:

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