{"id":6048,"url":"https://alion.io/job/twilio-machine-learning-engineer","title":"Machine Learning Engineer","company":{"id":1829,"name":"Twilio","domain":"twilio.com","url":"https://alion.io/company/twilio","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"A","score":90,"open_postings":26,"ghost_share":0,"stale_share":0.385,"repost_share":0.038,"time_to_fill_p50_days":49,"computed_at":"2026-10-17T05:46:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"junior","employment_type":null,"work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Ireland"],"countries":["IE"],"hiring_countries":["IE"],"hiring_countries_total":1,"salary":null,"salary_estimate":null,"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"AutoGen","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CrewAI","optional":false},{"name":"Fine-tuning","optional":false},{"name":"GCP","optional":false},{"name":"Hugging Face","optional":false},{"name":"JAX","optional":false},{"name":"LangGraph","optional":false},{"name":"LLM","optional":false},{"name":"LLMOps","optional":false},{"name":"Machine Learning","optional":false},{"name":"NLP","optional":false},{"name":"NLTK","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"TensorFlow","optional":false},{"name":"Transformers","optional":false},{"name":"Twilio","optional":false},{"name":"LangChain","optional":true}],"status":"live","first_seen_at":"2026-06-18T17:31:02Z","employer_posted_date":"2026-10-09","last_verified_at":"2026-10-18T06:12:09Z","board_verified":true,"closed_at":null,"days_open":121,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":121},"description":"Who we are \nAt Twilio, we’re shaping the future of communications, all from the comfort of our homes. We deliver innovative solutions to hundreds of thousands of businesses and empower millions of developers worldwide to craft personalized customer experiences.\nOur 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.\n.\nHiring and how we work\nWe use Artificial Intelligence (AI) to help make our hiring process efficient. That said, every hiring decision is made by real Twilions! \nAlso, while we are a remote-first company, you may be asked to report in person on an ad-hoc basis for team gatherings, functional off-sites or customer meetings. \n.\nSee yourself at Twilio\nJoin the team as Twilio’s next Machine Learning Engineer.\nAbout the job\nThis 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.\nResponsibilities\nIn this role, you’ll:\nDesign and development of machine learning solutions, ensuring accuracy, performance, security, and scalability.\nImplement 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\nInstrument AI/ML services with appropriate metrics, logging, and telemetry to monitor model performance and operational health against defined SLOs\nParticipate in on-call rotations, executing progressive rollouts and applying standard mitigation strategies to keep production inference services healthy\nCollaborate across planning, design, and code review phases contributing to product and technical discussions, while helping raise overall code quality through thoughtful review feedback\nQualifications \nTwilio values diverse experiences from all kinds of industries, and we encourage everyone who meets the required qualifications to apply. If your career is just starting or hasn't followed a traditional path, don't let that stop you from considering Twilio. We are always looking for people who will bring something new to the table!\n*Required:\nBachelor's degree in Computer Science, Mathematics, Statistics, or a related quantitative field, or equivalent practical experience\n2+ 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.\nExperience 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)\nProficiency in Python (preferred) or similar OO language.\nExperience utilizing Large (or Small) Language Models within software systems.\nExcellent written and verbal communication skills with the ability to articulate complex technical concepts to both technical and non-technical audiences.\nDesired:\nHands-on experience with conversational AI, or LLM fine-tuning and prompt engineering in a production context\nExposure to agentic AI frameworks such as LangGraph, AutoGen, CrewAI\nFamiliarity with MLOps/LLMOps tooling related to maintaining models in production such as testing, versioning, model registry, retraining, and monitoring.\nLocation\nThis role will be remote from Ireland.\nTravel \nWe 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.\nWhat We Offer\nWorking 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.\nTwilio thinks big. Do you?\nWe like to solve problems, take initiative, pitch in when needed, and are always up for trying new things. That's why we seek out colleagues who embody our values - something we call Twilio Magic. Additionally, we empower employees to build positive change in their communities by supporting their volunteering and donation efforts.\nSo, if you're ready to unleash your full potential, do your best work, and be the best version of yourself, apply now! If this role isn't what you're looking for, please consider other open positions.\n.\nStay alert to recruitment fraud\nWe care about your safety. Scammers sometimes impersonate Twilio recruiters through fake job postings, emails, websites, or messages. Please ensure you are engaging with an official @twilio.com email address. We will never ask for payment, gift cards, cryptocurrency, or banking information during the recruiting process. We do not make job offers without a formal interview process or conduct interviews exclusively through text-based messaging apps.\n.\nTwilio is proud to be an equal opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Qualified applicants with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. 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