Machine Learning Engineer
Remote - Ireland
- Pay
- Salary not listed in the saved posting
- Work setup
Remote stated — work setup source
Location This role will be remote from Ireland. Travel
Listed location: Remote - Ireland
Read the full posting- Employment
- Unconfirmed
What you’ll work on
Full postingDesign and build machine learning solutions for accuracy, performance, security and scale
Build and maintain end-to-end ML pipelines, from data ingestion to production deployment
Instrument ML services with metrics, logging and telemetry against defined SLOs
Take part in on-call rotations and run progressive rollouts for production inference services
Contribute to product and technical discussions and code reviews
From the employer’s posting
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
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
What you’ll bring
All qualificationsCore experience
- Bachelor's degree in Computer Science, Mathematics, Statistics, or a related quantitative field, or equivalent practical experience
- Hands-on experience with conversational AI, or LLM fine-tuning and prompt engineering in a production context
- 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.
- Familiarity with MLOps/LLMOps tooling related to maintaining models in production such as testing, versioning, model registry, retraining, and monitoring.
- 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.
Qualification wording
Bachelor's degree in Computer Science, Mathematics, Statistics, or a related quantitative field, or equivalent practical experience
Hands-on experience with conversational AI, or LLM fine-tuning and prompt engineering in a production context
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.
Familiarity with MLOps/LLMOps tooling related to maintaining models in production such as testing, versioning, model registry, retraining, and monitoring.
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.
Education & alternatives
*Required: - 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.
Tools in this posting
- Python
- AWS
- Azure
- Google Cloud (GCP)
- Huggingface
- PyTorch
- TensorFlow
- Transformers
Source — Tool mentions in context
- 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)
- 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.
- 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.
Benefits in the posting
Full benefits wording- 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.
- Stay alert to recruitment fraud
From the employer’s posting.
About Twilio
At Twilio, we’re shaping the future of communications, all from the comfort of our homes.
In the employer’s words · Read in context
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Jun 18, 2026 · 122d ago
- Recorded sightings
- 169
- Last seen by us
- Oct 17, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
Job description
Who we are
At 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.
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.
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Hiring and how we work
We use Artificial Intelligence (AI) to help make our hiring process efficient. That said, every hiring decision is made by real Twilions!
Also, 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.
.
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
Qualifications
Twilio 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!
*Required:
- 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.
Location
- This role will be remote from Ireland.
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.
What We Offer
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.
Twilio thinks big. Do you?
We 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.
So, 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.
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Stay alert to recruitment fraud
We 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.
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Twilio 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. Additionally, Twilio participates in the E-Verify program in certain locations, as required by law.
Your next step
- Have your CV and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the salary range before committing time to the process.
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Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
Remote - Ireland
At 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. 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. . Hiring and how we work
More source context
We use Artificial Intelligence (AI) to help make our hiring process efficient. That said, every hiring decision is made by real Twilions! Also, 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. . See yourself at Twilio
More relevant text appears in the full description.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
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