Jobgether
AI/ML Research Engineer

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Job Opportunity: AI/ML Research Engineer
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an AI/ML Research Engineer based in the United Kingdom.
This role sits at the intersection of applied research and production-grade AI engineering, focusing on the design and deployment of advanced agentic AI systems and LLM-powered applications. You will contribute to building intelligent, scalable solutions that transform enterprise data into actionable insights and autonomous workflows. Working in a fast-paced, collaborative environment, you will experiment with cutting-edge AI frameworks, evaluate model performance across providers, and help shape next-generation AI assistant products. The role blends research thinking with hands-on engineering, requiring strong execution skills and curiosity for emerging AI paradigms. You will also work with complex enterprise-scale data systems and cloud environments to ensure robust, production-ready AI solutions.
Accountabilities
- Design, develop, and deploy agentic AI systems and LLM-based applications with a focus on scalability, performance, and reliability.
- Build and optimize AI/ML models using Python, including prompt engineering and integration with modern LLM frameworks.
- Develop AI assistant-style and agent-based applications that automate complex workflows and decision-making processes.
- Work with large-scale enterprise data systems and databases such as SAP HANA, DB2, and SQL Server, leveraging advanced SQL for data processing and analysis.
- Evaluate and select appropriate AI models (e.g., OpenAI, Meta, or others) based on use case requirements and performance trade-offs.
- Collaborate with cross-functional teams to design architecture, integrate models, and deploy solutions in cloud environments.
- Support the development and scaling of AI solutions in enterprise-grade environments, ensuring robustness and maintainability.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
See breakdownIt searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Requirements
- Bachelor’s degree in Computer Science, Data Science, Systems Engineering, or a related field, or equivalent practical experience.
- Strong hands-on experience in Python and prompt engineering for large language models (LLMs).
- Proven experience building agentic AI systems or AI assistant-style applications.
- Solid understanding of Natural Language Processing (NLP) and deploying scalable machine learning models.
- Strong SQL expertise and experience working with enterprise databases such as SAP HANA, DB2, and SQL Server.
- Experience working in large-scale enterprise data environments or comparable systems.
- Familiarity with cloud AI/ML platforms and relevant certifications (e.g., Azure AI Engineer, AWS ML) is highly desirable.
- Experience with Model Context Protocol (MCP), predictive modeling, or Node.js is a plus.
- Strong problem-solving mindset with the ability to work in fast-paced, collaborative environments.
- Ability to evaluate trade-offs between different AI models and architectures based on business and technical needs.
Benefits
- Opportunity to work on cutting-edge AI research and agentic AI systems.
- Exposure to large-scale enterprise data environments and advanced AI infrastructure.
- Collaborative, innovation-driven engineering culture.
- Hands-on experience with leading LLM providers and emerging AI frameworks.
- Strong opportunities for learning, experimentation, and professional growth.
- Flexible and dynamic work environment focused on impact and innovation.


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How Jobgether Works
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Why Apply Through Jobgether?
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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