At a Glance
- Tasks: Lead the data-to-production lifecycle for ML models and ensure robust pipelines.
- Company: Fast-scaling AI-first software business pushing boundaries in intelligent software.
- Benefits: Competitive salary, hybrid working, and a culture of mentorship and technical excellence.
- Other info: Join a close-knit team dedicated to innovation and professional growth.
- Why this job: Own the ML platform strategy and work on cutting-edge AI technologies.
- Qualifications: 5+ years in data engineering and MLOps, strong Python skills, and cloud experience.
The predicted salary is between 95000 - 110000 £ per year.
Senior individual contributor role at a scaling AI-first software business. Own the full data-to-production lifecycle across ML models, agents and platform infrastructure. Belfast based, hybrid working. Salary £95,000 to £110,000. UK work authorisation required.
About the Company
Our client is a fast-scaling, AI-first software business building cutting-edge agent and LLM-based systems at scale. With a cross-functional engineering team and a genuine commitment to technical excellence, this is an environment where senior data professionals can take real ownership of complex, meaningful problems. The Belfast team sits at the heart of the company's AI engineering capability, working on challenges that are shaping the future of intelligent software.
The Role
A newly created senior role bridging the gap between machine learning research and high-scale production systems. You will own the full data-to-production lifecycle, turning complex experimental models and agentic workflows into robust, reproducible pipelines. Alongside delivery, you will establish observability standards, lead deployment practices, contribute to platform roadmap development and mentor engineers across the team. This role suits someone equally comfortable in the weeds of a training pipeline and setting technical direction for a growing platform.
Key Responsibilities
- Build and maintain reliable, reproducible pipelines for training data, feature generation and embeddings.
- Partner with data scientists to make training pipelines robust and easy to iterate on.
- Own reliability, monitoring and incident response for ML models and agents in production, including CI/CD, versioning, canary deployment and rollback.
- Build observability into ML services covering latency, error rates, drift detection and quality regressions.
- Contribute to the one to two year roadmap for the data and ML platform.
- Set engineering standards, conduct design reviews and mentor engineers on production-grade practices.
- Work closely with infrastructure and release teams, absorbing ML serving and pipeline work across the team.
What You'll Need
Essential:
- Bachelor's degree in Computer Science, Engineering or a related field, or equivalent practical experience.
- 5 or more years across data engineering and ML production engineering, including 2 or more years in MLOps or ML production systems.
- Hands-on production experience with Google Cloud Platform, specifically Vertex AI and BigQuery.
- Strong experience building data and feature pipelines for ML training.
- Experience with ML pipeline tooling such as MLflow, Kubeflow or Vertex AI, and CI/CD for model lifecycle management.
- Experience with Docker, Kubernetes and cloud infrastructure.
- Proven track record owning production incidents including detection, mitigation and rollback.
- Strong Python, Go or Java fundamentals.
- Experience mentoring engineers and influencing technical direction.
Desirable:
- Experience operating LLM or agent-based systems in production including LLMOps.
- Direct experience partnering with data scientists on feature engineering or model training.
- Master's degree in a relevant field.
Why Apply?
- Salary of £95,000 to £110,000.
- Newly created senior role with full ownership of ML platform strategy and production reliability.
- Work at the cutting edge of MLOps, LLM deployment and agentic AI in production.
- Close-knit engineering team with a strong culture of technical excellence and mentorship.
- Belfast based at a business genuinely pushing the boundaries of intelligent software.
Interested?
Senior Data Scientist (AI/ML) in Belfast employer: Ocho
Join a forward-thinking UK technology company that is at the forefront of AI innovation, where you will have the opportunity to develop your skills in a supportive and fast-paced environment. With a strong emphasis on mentorship from senior engineers, flexible working patterns, and the chance to own your projects early on, this role offers a unique pathway for professional growth in AI engineering. The company's commitment to an AI-first culture ensures that you will be working with cutting-edge tools and technologies, making a real impact in complex customer environments.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Scientist (AI/ML) in Belfast
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Ocho!
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Ocho.
✨Apply Directly through Our Website
When you find a suitable opening like Senior Data Scientist (AI/ML) at Ocho, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Senior Data Scientist (AI/ML) in Belfast
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Ocho, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Ocho. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Ocho
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Ocho!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
