At a Glance
- Tasks: Build and optimise AI and NLP solutions that transform digital customer experiences.
- Company: Join a forward-thinking tech partner focused on innovation and collaboration.
- Benefits: Enjoy competitive salary, unlimited PTO, and fully remote work options.
- Other info: Collaborative culture with opportunities for continuous learning and career growth.
- Why this job: Make a real impact with cutting-edge AI technologies in a fast-growing environment.
- Qualifications: 3+ years in AI/NLP, strong software engineering skills, and experience with machine learning frameworks.
The predicted salary is between 60000 - 80000 £ per year.
This position is listed on behalf of a partner company that manages all applications and next steps. Our partner is looking for an AI/NLP/Data Engineer based in the United Kingdom.
This role offers the opportunity to build advanced AI and natural language processing solutions that transform digital customer experiences.
You will design, develop, and optimize machine learning models, data pipelines, and intelligent automation systems that support real-world business applications.
Working at the intersection of AI research and production engineering, you will help create scalable solutions using modern technologies and cloud infrastructure.
The position combines technical innovation, experimentation, and hands‑on development to bring AI capabilities from concept to deployment.
You will collaborate with engineering teams to improve model performance, build reliable AI platforms, and solve complex data challenges.
This is an exciting opportunity for an AI‑focused engineer passionate about creating practical, impactful machine learning solutions in a fast‑growing environment.
- Accountabilities
- Build, improve, and deploy NLP, generative AI, and machine learning models that support intelligent digital engagement solutions.
- Develop scalable infrastructure for AI modeling, experimentation, training, deployment, monitoring, and continuous improvement.
- Design and maintain data processing pipelines, AI trainer tools, and workflows that enable efficient model development.
- Research, prototype, and implement algorithmic improvements to enhance model accuracy, performance, and scalability.
- Develop machine intelligence solutions tailored to customer needs and industry‑specific use cases.
- Monitor, debug, and optimize AI models running in production environments.
- Collaborate with platform and engineering teams to create tools and capabilities that accelerate AI development and deployment.
- Contribute to technical documentation, knowledge sharing, and internal training initiatives related to AI and machine learning.
- Make thoughtful technology decisions that balance innovation, scalability, and business impact.
Requirements
- 3+ years of experience in AI, machine learning, NLP, data engineering, or related technical fields.
- Master's degree or equivalent experience in Artificial Intelligence, Machine Learning, Natural Language Processing, Computer Science, or a related discipline.
- Proven experience building production‑quality AI systems involving generative AI, NLP, speech processing, deep learning, or similar technologies.
- Strong software engineering skills with experience developing reliable, scalable applications.
- Experience designing and deploying machine learning models with limited training data.
- Strong understanding of AI/ML development workflows, experimentation frameworks, and model deployment practices.
- Ability to quickly learn new technologies, research emerging techniques, and turn ideas into production‑ready solutions.
- Experience working with Python and machine learning frameworks such as Py Torch.
- Familiarity with cloud environments such as AWS or Google Cloud Platform.
- Experience with technologies such as Linux, Airflow, Docker, or Node. js is a plus.
- Strong communication skills with the ability to collaborate effectively in a dynamic, cross‑functional environment.
- Passion for improving AI systems and building robust, scalable machine learning solutions.
Benefits
- Competitive salary package with equity opportunities.
- Comprehensive medical, dental, and vision benefits.
- Unlimited paid time off policy.
- Fully remote work-from-home opportunity.
- Access to modern development tools, hardware, and collaboration platforms.
- Opportunity to work with cutting‑edge AI, NLP, and machine learning technologies.
- Collaborative team environment focused on innovation and continuous learning.
- Opportunity to make a significant impact by developing practical AI solutions at scale.
- #J-18808-Ljbffr
AI/NLP/Data Engineer employer: Jobgether
At Jobgether, we pride ourselves on being an exceptional employer that fosters a collaborative and innovative work culture. Our remote working environment allows for flexibility while providing ample opportunities for professional growth and development in the tech industry. Join us to make a meaningful impact in enhancing open-source technology adoption, all while enjoying the benefits of a supportive team and a commitment to your career advancement.
StudySmarter Expert Advice🤫
We think this is how you could land AI/NLP/Data Engineer
✨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 Jobgether!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like AI/NLP/Data Engineer at Jobgether.
✨Leverage Professional Networks
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 Jobgether.
✨Apply Directly through Our Website
When you find a suitable opening like AI/NLP/Data Engineer at Jobgether, 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 AI/NLP/Data Engineer
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 Jobgether, 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 Jobgether. 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 Jobgether
✨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 Jobgether!
✨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.
