Machine Learning Engineer

Overview¿Listo para inscribirse?Antes de hacerlo, asegúrese de leer todos los detalles pertenecientes a este trabajo en la descripción a continuación.As Twilio’s Machine Learning Engineer on the Conversation Intelligence team, you design AI-powered features to make customer conversations smarter.You will build and deploy end-to-end ML solutions at scale, collaborating with experienced practitioners to ship real features from pipelines to production inference.You’ll monitor performance against SLOs and contribute to code quality through thoughtful reviews.This role blends impactful ML work with a remote-first culture and global collaboration.Compensaciones / Beneficioscompetitive paygenerous time offparential and wellness leavehealthcareretirement savings programResponsabilidadesDesign and develop ML solutions ensuring accuracy, performance, security, and scalabilityBuild and maintain end-to-end AI/ML pipelines from data ingestion to deploymentInstrument services with metrics, logging, and telemetry to monitor model health against SLOsParticipate in on-call rotations and manage production inference health with progressive rolloutsCollaborate across planning, design, and code reviews to raise overall code qualityRequisitos principales2+ years of experience in ML engineering or applied MLProficiency in Python and at least one ML framework (PyTorch, TensorFlow, xkdbapo or JAX)Familiarity with NLP libraries such as Hugging Face Transformers, NLTK, or SpaCyExperience deploying ML services in cloud environments (AWS, GCP, or Azure)Experience working with Large Language Models within software systemsExcellent written and verbal communication skillsclear communicationteam collaborationproblem solvingPythonPyTorchTensorFlow

Requisitos principales2+ years of experience in ML engineering or applied ML Proficiency in Python and at least one ML framework (PyTorch, TensorFlow, xkdbapo or JAX) Familiarity with NLP libraries such as Hugging Face Transformers, NLTK, or SpaCy Experience deploying ML services in cloud environments (AWS, GCP, or Azure) Experience working with Large Language Models within software systems Excellent written and verbal communication skills clear communication team collaboration problem solving