Machine Learning Engineer
Core
Design and engineer AI-powered features to extract meaning from voice and messaging data at scale, making customer conversations smarter.
Role type
Machine Learning Engineer (Conversation Intelligence)
Builds
Production ML pipelines, model inference services, and AI features for customer communication platforms
Domain
Telecommunications / Conversational AI / NLP
Deliverable
production ML models
Required skills
Python, PyTorch/TensorFlow/JAX, NLP libraries (Hugging Face, NLTK, SpaCy), LLM integration, cloud infrastructure (AWS/GCP/Azure), model versioning, experiment tracking
Preferred skills
Conversational AI, LLM fine-tuning, prompt engineering, agentic AI frameworks (LangGraph, AutoGen, CrewAI), MLOps/LLMOps tooling
Technologies
Python, PyTorch, TensorFlow, JAX, Hugging Face, NLTK, SpaCy, AWS, GCP, Azure, LangGraph, AutoGen, CrewAI
Responsibilities
Design and develop machine learning solutions ensuring accuracy, performance, security, and scalability; Implement and maintain end-to-end AI/ML pipelines from data ingestion to deployment; Instrument AI/ML services with metrics and telemetry to monitor performance against SLOs; Participate in on-call rotations for production inference services; Collaborate on planning, design, and code review phases
Seniority
Mid-level, hands-on IC