At a Glance
- Tasks: Build and deploy cutting-edge AI/ML models that transform consumer feedback into actionable insights.
- Company: Join a globally recognised Great Place to Work with a vibrant culture.
- Benefits: Enjoy hybrid working, competitive salary, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on innovation and career advancement.
- Why this job: Work on real production-scale ML projects and explore LLMs and generative AI.
- Qualifications: 5+ years in machine learning, strong Python skills, and experience with NLP.
The predicted salary is between 63000 - 77000 Β£ per year.
AI/ML Engineer Belfast (Flexible Hybrid) | Full-time
Build the AI/ML models that turn billions of pieces of consumer feedback into trustworthy insight. Work directly on NLP, personalisation and content-quality models at genuine production scale using a Python/cloud stack, with real scope to bring in LLMs and generative AI.
About the Company
Since 2005, this business has grown from a single office into a global operation spanning North America, Europe, Asia and Australia, now connecting thousands of brands and retailers with billions of consumers through user-generated content at genuinely massive scale. That scale is exactly why AI and ML sit at the centre of the product, not on the sidelines, and the company's culture has been externally recognised as a Great Place to Work in the US, Australia, India, Lithuania, France, Germany and the UK.
The Role
You'll join a team using machine learning to make sense of an enormous, constantly growing volume of reviews, questions and user-generated content, from spotting low-quality or fraudulent content to powering personalisation and search relevance for shoppers. It's a role with real production exposure: your models won't sit in a notebook, they'll run against live consumer traffic, at a scale most engineers never get to work at.
Key Responsibilities
- Design, train and deploy ML models for content moderation, quality scoring and personalisation
- Apply NLP techniques to extract insight and structure from unstructured consumer content
- Evaluate and integrate LLMs and generative AI where they add genuine product value
- Build and maintain robust MLOps pipelines for training, deployment and monitoring
- Partner with data engineering to ensure models are fed clean, reliable data at scale
- Monitor live model performance and iterate based on real production feedback
- Collaborate with product and engineering teams to translate ML capability into shipped features
Essential:
- 5+ years building and deploying machine learning models in production environments
- Strong Python skills and experience with ML frameworks such as PyTorch or TensorFlow
- Practical experience with NLP techniques and unstructured text data
- Experience with a public cloud provider (AWS, GCP or Azure) for ML workloads
- Solid understanding of MLOps: model deployment, monitoring and retraining pipelines
- Strong analytical thinking and the ability to communicate ML concepts to non-technical teams
Desirable:
- Hands-on experience with LLMs or generative AI in a production setting
- Experience with recommendation systems or personalisation at scale
Why Apply?
- Hybrid working model based in Belfast
- Genuine production-scale ML, not proof-of-concept work
- Direct exposure to LLMs and generative AI applications
- A company independently certified as a Great Place to Work in seven countries
- A culture that rewards curiosity and staying ahead of emerging AI techniques
Next Steps
Interested, or know someone who'd be a great fit? Get in touch with Chanel for a confidential chat.
Senior AI/ML Engineer (Exclusive) TLNT1_NI in Belfast employer: Ocho
Join a dynamic and innovative digital consultancy that champions a remote-first work culture, offering exceptional benefits such as a competitive salary, generous annual leave, and a commitment to professional development. With a focus on quality and collaboration, you'll thrive in an environment that values your expertise and provides the autonomy to shape QA processes while working on complex, multi-component systems alongside a talented team in Northern Ireland.