About The Role Build and deploy NLP models and chatbot systems. You'll work with LLMs, implement RAG architectures, and create evaluation frameworks for conversational AI systems.
What You'll Do Design and implement RAG (Retrieval-Augmented Generation) systems Build and fine-tune LLMs for specific use cases Develop chatbot architectures and conversation flows Implement model evaluation and monitoring frameworks Optimize model performance and reduce inference costs Create data pipelines for training and inference Collaborate with product teams on AI feature requirements What You'll Bring 4+ years of ML engineering experience with focus on NLP Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow)
Experience with transformer models and large language models Knowledge of vector databases and semantic search Understanding of MLOps practices and model deployment Experience with cloud ML platforms (SageMaker, Vertex AI) Solid background in statistics and machine learning theory Nice to Have Experience with prompt engineering and fine-tuning techniques Knowledge of multi-modal models (vision + language) Familiarity with reinforcement learning from human feedback (RLHF) Understanding of distributed training and model parallelism Why Join StackBinary™? Flexible working hours Remote-friendly culture Learning & development budget High-ownership projects Pragmatic engineering culture Work with cutting-edge tech Ready to Apply? Join our team of builders who love shipping quality software.