Jobgether
AI/ML Specialist Solutions Architect

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AI/ML Specialist Solutions Architect
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 Specialist Solutions Architect based in United Kingdom.
Join a pioneering AI infrastructure environment where you will help organizations design and deploy scalable machine learning solutions. This role combines deep technical expertise with customer-facing collaboration, allowing you to influence how businesses leverage advanced AI platforms. You will act as a trusted advisor, guiding customers through complex AI workloads, distributed training environments, and production-scale deployments. Working closely with engineering and product teams, you will translate customer challenges into impactful solutions and product improvements. This opportunity is ideal for an experienced AI professional who enjoys solving complex problems, sharing knowledge, and shaping the future of AI adoption.
Accountabilities
- Design customer-focused AI and machine learning solutions that maximize business value and align with technical and strategic objectives.
- Act as a trusted technical advisor for customers, helping them successfully adopt and scale AI infrastructure and services.
- Architect and support large-scale AI deployments, including distributed training environments involving multi-node and multi-GPU systems.
- Build strong customer relationships by understanding technical requirements, addressing challenges, and ensuring long-term satisfaction.
- Deliver technical content including presentations, documentation, whitepapers, manuals, and webinars for audiences with different levels of technical expertise.
- Collaborate closely with engineering and product teams to communicate customer feedback, influence priorities, and improve solutions.
- Support customers in moving AI workloads from experimentation and proof-of-concept stages into reliable production environments.
- Stay current with AI/ML technologies, frameworks, and infrastructure trends to provide high-quality technical guidance.
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
- 3+ years of experience working with cloud technologies in MLOps engineering, machine learning engineering, solutions architecture, or similar technical roles.
- Strong understanding of machine learning ecosystems, including models, AI use cases, workflows, and supporting tooling.
- Proven experience designing, deploying, and optimizing distributed training pipelines across multi-node and multi-GPU environments.
- Hands-on experience with machine learning frameworks such as PyTorch, JAX, TensorFlow, Hugging Face, or similar technologies.
- Strong knowledge of cloud infrastructure, DevOps practices, and modern AI deployment approaches.
- Experience with programming languages such as Python, Go, Java, or C++.
- Familiarity with technologies including Kubernetes, Slurm, Docker, Helm, Git, Terraform, and infrastructure-as-code practices.
- Excellent written and verbal communication skills, with the ability to explain complex technical concepts to both technical and non-technical audiences.
- Experience deploying production inference infrastructure or scaling ML pipelines from prototypes to production is considered a strong advantage.
Benefits
- Competitive compensation package.
- Opportunity to work on impactful AI infrastructure projects shaping the future of machine learning.
- Flexible work options, including remote opportunities across Europe.
- High level of ownership and autonomy in a fast-growing technology environment.
- Career development opportunities with continuous learning and exposure to advanced AI technologies.
- Collaboration with talented international teams of engineers and AI specialists.
- Innovative culture focused on experimentation, growth, and meaningful impact.


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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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