Machine Learning Engineer (NLP/Chatbots)
Indexed description
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)
Strong 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
What You'd Build
These aren't hypothetical projects, they're live products you can try before your first interview.
AI Call Center & AI Receptionist, Voice AI that answers business calls in 11 languages and logs every conversation.
Sales Intelligence Engine, Finds companies, people and numbers, then tells reps what to pitch.
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?
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