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Machine Learning Engineer
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Machine Learning Engineer based in the United Kingdom.
As a Machine Learning Engineer, you will play a key role in developing and scaling production-grade AI systems that power advanced, real-world applications. This hands-on position offers the opportunity to own the full machine learning lifecycle, from data preparation and model training to deployment, monitoring, and continuous optimization. Working in a fast-paced and collaborative environment, you will transform cutting-edge research into reliable, high-performing solutions that deliver measurable value to users. You will collaborate closely with research, engineering, and product teams while helping shape robust, scalable machine learning infrastructure and mentoring fellow engineers. This is an excellent opportunity for someone passionate about building impactful AI systems that perform reliably at scale.
Accountabilities
- Design, develop, and maintain production-ready machine learning systems supporting advanced AI-powered products.
- Own the complete machine learning lifecycle, including data preparation, model training, evaluation, deployment, inference, monitoring, and continuous improvement.
- Translate research concepts into scalable, reliable production solutions that meet business and technical objectives.
- Investigate, troubleshoot, and resolve model performance issues and production incidents using real-world data and operational insights.
- Continuously optimize machine learning models for accuracy, latency, scalability, reliability, efficiency, and operational cost.
- Collaborate closely with cross-functional teams to integrate machine learning capabilities into production products.
- Mentor other machine learning engineers through technical guidance, code reviews, and knowledge sharing.
- Build and maintain robust training, inference, and data pipelines while ensuring system stability under production constraints.
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.
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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
- Proven experience designing, developing, and deploying machine learning systems used in production environments.
- Strong expertise in Python and deep learning frameworks such as PyTorch and/or JAX.
- Hands-on experience with GPU-based training and inference systems, including performance optimization and large-scale model deployment.
- Solid understanding of modern machine learning models, their behavior in production, and strategies for identifying and resolving failure modes.
- Experience writing clean, maintainable, and production-quality software with a systems-oriented engineering mindset.
- Ability to independently manage projects from concept through deployment while balancing speed, quality, and reliability.
- Strong analytical and problem-solving skills with an iterative, data-driven approach to improving machine learning performance.
- Excellent communication and collaboration skills, with experience working alongside research, engineering, and product teams.
- Previous mentoring or technical leadership experience is considered an advantage.


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Benefits
- Fully remote full-time position with the flexibility to work from Europe.
- Opportunity to work on innovative AI products solving complex real-world challenges.
- High level of ownership and autonomy in a technically ambitious environment.
- Collaboration with a highly skilled, multidisciplinary team focused on engineering excellence.
- Exposure to cutting-edge machine learning technologies and large-scale AI systems.
- Transparent and efficient recruitment process with timely communication throughout.
- Strong opportunities for professional development and long-term career growth.
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.
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