Machine Learning Engineer

TWILIO
Murcia, Spain
2 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours

Tech stack

Artificial Intelligence Amazon Web Services Microsoft Azure Software Quality Code Review Python (Programming Language) Machine Learning NLTK (NLP Analysis) Tensorflow Azure Machine Learning Twilio Data Logging
+8 more
Cloud Platform System Data Ingestion Pytorch Large Language Models Build Management HuggingFace Performance Monitor Machine Learning Operations

Job description

OverviewAs 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, 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

Requirements

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, 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

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Good distractions

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