Machine Learning Engineer

Twilio
San Francisco, United States of America
4 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Intermediate
Compensation
€ 60K

Job location

Remote
Barcelona, Spain

Tech stack

Artificial Intelligence
Amazon Web Services (AWS)
Azure
Software Quality
Code Review
Python
Machine Learning
Language Modeling
NLTK
TensorFlow
Azure
Software Systems
Twilio
Management of Software Versions
Data Logging
Cloud Platform System
Feature Engineering
Chatbots
Data Ingestion
PyTorch
Large Language Models
Prompt Engineering
Information Technology
HuggingFace
Machine Learning Operations
Spacy
Software Version Control

Job description

Our dedication to remote-first work, and strong culture of connection and global inclusion means that no matter your location, you're part of a vibrant team with diverse experiences making a global impact each day. As we continue to revolutionize how the world interacts, we're acquiring new skills and experiences that make work feel truly rewarding. Your career at Twilio is in your hands. We use Artificial Intelligence (AI) to help make our hiring process efficient. That said, every hiring decision is made by real Twilions! . See yourself at Twilio Join the team as Twilio's next Machine Learning Engineer. About the job This position is to design and engineer AI powered features that makes every customer conversation smarter. As a Machine Learning Engineer on the Conversation Intelligence team, you'll develop and deploy solutions that extract meaning from voice and messaging data at Twilio scale. You'll work alongside experienced ML practitioners to ship real features - from model pipelines to production inference - that directly shape how businesses understand their customers. Responsibilities In this role, you'll:

  • Design and development of machine learning solutions, ensuring accuracy, performance, security, and scalability.
  • Implement and maintain end-to-end AI/ML pipelines - from data ingestion and feature engineering through to model development, validation, and deployment with guidance from senior engineers on complex architectural decisions
  • Instrument AI/ML services with appropriate metrics, logging, and telemetry to monitor model performance and operational health against defined SLOs
  • Participate in on-call rotations, executing progressive rollouts and applying standard mitigation strategies to keep production inference services healthy
  • Collaborate across planning, design, and code review phases contributing to product and technical discussions, while helping raise overall code quality through thoughtful review feedback, 1. This role will be remote from Spain. Travel We prioritize connection and opportunities to build relationships with our customers and each other. For this role, you may be required to travel occasionally to participate in project or team in-person meetings.

Requirements

  • Bachelor's degree in Computer Science, Mathematics, Statistics, or a related quantitative field, or equivalent practical experience

  • 2+ years of experience in machine learning engineering or applied ML, with demonstrated proficiency in Python and at least one ML framework (PyTorch, TensorFlow, or JAX) and familiarity with NLP libraries such as Hugging Face Transformers, NLTK, or SpaCy.

  • Experience developing, testing, and deploying small-to-medium scoped ML services or features in a collaborative engineering environment, including model versioning, experiment tracking, and cloud-based infrastructure (AWS, GCP, or Azure)

  • Proficiency in Python (preferred) or similar OO language.

  • Experience utilizing Large (or Small) Language Models within software systems.

  • Excellent written and verbal communication skills with the ability to articulate complex technical concepts to both technical and non-technical audiences. Desired:

  • Hands-on experience with conversational AI, or LLM fine-tuning and prompt engineering in a production context

  • Exposure to agentic AI frameworks such as LangGraph, AutoGen, CrewAI

  • Familiarity with MLOps/LLMOps tooling related to maintaining models in production such as testing, versioning, model registry, retraining, and monitoring.

Benefits & conditions

Working at Twilio offers many benefits, including competitive pay, generous time off, ample parental and wellness leave, healthcare, a retirement savings program, and much more. Offerings vary by location.

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