At a Glance
- Tasks: Develop and deploy cutting-edge machine learning models to solve real-world problems.
- Company: Well-funded tech company focused on next-gen AI products.
- Benefits: Competitive salary, bonus, and comprehensive benefits package.
- Other info: Dynamic environment with opportunities for growth and innovation.
- Why this job: Join a talented team and shape the future of intelligent decision-making systems.
- Qualifications: Experience in building ML models and strong Python skills required.
The predicted salary is between 63000 - 77000 £ per year.
About the Company
I'm partnering with a well-funded technology company building next-generation AI products and looking for an experienced ML / Data Engineer to help shape the future of intelligent decision-making systems.
About the Role
This is an opportunity to work at the intersection of
- Machine Learning
- Computer Vision
- Generative AI
- Large Language Models
- Production AI Engineering
The Role You'll be responsible for developing, evaluating and deploying machine learning models that solve complex real-world problems at scale.
Working alongside a highly technical team of engineers and researchers, you'll help design intelligent systems that combine multiple AI approaches, balancing performance, reliability and operational efficiency.
Responsibilities
Key responsibilities include
- Developing and improving machine learning and deep learning models
- Building evaluation frameworks to measure model performance
- Fine-tuning and deploying open-source AI models
- Developing production-grade AI solutions using frontier-model APIs
- Designing data-driven feedback loops to continuously improve system performance
- Collaborating with software engineers to deploy scalable ML systems
Qualifications
- Commercial experience building and deploying ML models
- Required Skills
What We're Looking For
- Commercial experience building and deploying ML models
- Strong Python skills (Py Torch, Num Py, Pandas, Open CV, SQL)
- Experience working with LLMs, Gen AI, or multimodal AI systems
- Production experience integrating external AI APIs
- Understanding of model evaluation, experimentation and optimisation
- Experience with Docker, CI/CD and software engineering best practices
- Preferred Skills
- Nice to Have
- Computer Vision experience
- Experience fine-tuning foundation models
- MLOps or platform engineering exposure
- Experience working with large-scale datasets
- Pay range and compensation package
- Competitive salary, bonus and benefits package
- Equal Opportunity Statement
- Interested in learning more? Get in touch -
ML / Data Engineer in Hull employer: Opus Recruitment Solutions
Join a forward-thinking company that values innovation and collaboration, offering a dynamic work culture where your contributions as a ServiceNow Mapping Product Lead will directly impact large-scale digital transformation initiatives. With a focus on employee growth, we provide ample opportunities for professional development and the chance to work alongside industry leaders in a hybrid environment that promotes work-life balance. Our commitment to excellence and support for your career aspirations make us an exceptional employer in the tech landscape.
Contact Details:
Opus Recruitment Solutions Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land ML / Data Engineer in Hull
✨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 Opus Recruitment Solutions!
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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 Opus Recruitment Solutions.
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We think you need these skills to ace ML / Data Engineer in Hull
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 Opus Recruitment Solutions, 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 Opus Recruitment Solutions. 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 Opus Recruitment Solutions
✨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 Opus Recruitment Solutions!
✨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.
