At a Glance
- Tasks: Design and support AI solutions that enhance national security and operational capabilities.
- Company: Join Rowden, a fast-growing engineering powerhouse in Bristol.
- Benefits: Flexible working, inclusive culture, and opportunities for professional growth.
- Other info: Embrace a dynamic environment with mentorship and career advancement.
- Why this job: Make a real impact by shaping AI systems for critical applications.
- Qualifications: Experience in AI/ML engineering and a passion for solution architecture.
The predicted salary is between 72000 - 88000 £ per year.
We're building the UK's next generation engineering powerhouse, providing critical technology that strengthens national security and resilience.
We specialise in turning advances in sensing, AI, and communications into operational capability for the edge, where connectivity may be degraded or denied.
Our work focuses on accelerating the deployment of technology, improving decision‑making for frontline teams, and protecting people and critical assets in demanding environments.
Headquartered in Bristol, Rowden employs around 200 people and operates over 20,000 square feet of engineering and manufacturing facilities.
We have a growing international footprint and are one of Europe's fastest-growing engineering businesses.
About the role
We are looking for an ML Solutions Architect to join our growing ML capability, designed for a capable AI or ML engineer who wants to move beyond pure implementation and start thinking at a systems and solution level.
You will work alongside senior architects on live programmes and pre‑sales engagements.
You will get structured exposure to the full arc of solution architecture, from shaping problem statements and designing AI pipelines through to supporting bids and engaging with customers, with direct mentorship and increasing ownership over time.
This is not a research role or a pure engineering role.
It suits someone who is technically strong, curious about how AI systems fit into larger operational contexts, and ready to start thinking about how solutions are designed, communicated, and delivered, not just built.
Candidates must be eligible for SC clearance.
More information about security clearance is available here
- Key areas of responsibility
- Support the design of end-to-end AI pipelines, from data ingestion and feature engineering through to model training, evaluation, deployment, and monitoring, contributing technical input and developing architectural judgement under senior guidance.
- Assist in the design and documentation of agentic AI systems, including tool use, orchestration, memory/context management, and LLM integration patterns.
- Support the integration of AI & ML solutions into wider systems, working with engineering teams to ensure AI components connect reliably with existing platforms and applications.
- Develop in-depth knowledge of the MLOps lifecycle, including retraining cadences, model versioning, drift detection, and rollback procedures, to support robust and reliable production AI systems.
- Contribute to technical proposals, architecture diagrams, and solution documentation for bids and pre‑sales engagements, working closely with senior architects.
- Research and assess tooling, platform, and hosting options, summarising trade‑offs clearly to inform architectural decisions.
- Support the identification of technical risks in AI solutions, including data quality issues, model drift, integration failure modes, and AI security and safety considerations.
- Work with ML engineers, data engineers, and domain SMEs to understand specialist constraints and incorporate them into solution designs.
- Develop your understanding of how AI solutions are scoped, costed, planned, and assured across the programme lifecycle.
- Gradually take on more ownership of discrete solution components as confidence and experience grow.
- Key skills, experience and behaviours
We are looking for someone with solid AI and ML engineering foundations who is ready to start applying that knowledge at a higher level.
We value potential and appetite as much as prior experience in architecture.
Essential
- Hands‑on experience as an AI or ML engineer. You have built, trained, and deployed models and understand what makes AI systems work in practice.
- Working knowledge of at least one of: agentic AI and LLM application patterns, ML model serving and monitoring, data pipeline design, or MLOps practices.
- Ability to think beyond implementation. You can ask “why are we building this?” and “how does this fit into the wider system?” as well as “how do we build it?”.
- Clear written and verbal communication. You can explain technical concepts to people who aren’t deeply in the weeds.
- Curiosity and a willingness to develop in areas outside your current specialism.
- Awareness of AI security and safety principles (e. g. secure data handling, access control, model risk), and a willingness to build this further given Rowden’s defence and national security context.
- Eligibility for SC clearance.
Desirable (not essential)
- Exposure to data platform patterns such as medallion or lakehouse architectures.
- Hands‑on experience with MLOps tooling or model‑serving infrastructure used to operationalise and scale ML systems.
- Any experience contributing to technical documentation, proposals, or solution designs, even informally.
- Familiarity with edge deployment constraints or resource‑limited inference environments.
- Experience in secure, regulated, or government‑adjacent environments.
About you
- You are technically grounded but starting to think beyond the code. You want to understand the full shape of a solution, not just your part of it.
- You communicate clearly and are comfortable articulating ideas to people at different levels.
- You are curious and self‑directed. You don’t wait to be told what to learn next.
- You are humble about what you don’t know, and you actively seek to close those gaps.
- You want a role where you are developed, not just deployed.
- You are ready to engage with customers and stakeholders, even if that’s new territory, and you see it as an opportunity.
- Working at Rowden
We are committed to building a flexible, inclusive, and enabling company. Our aim is to create a diverse team of talented people with unique skills, experience, and backgrounds!
We also recognise the importance of flexible working and support this wherever we can.
We typically operate a flexible, hybrid‑working model, with an average 3 days in the office each week (dependent on the role).
We welcome the opportunity to discuss flexibility, part‑time working requirements and/or workplace adjustments with all our applicants.
Rowden is a Disability Confident Committed company, and we actively encourage people with disabilities and health conditions to apply for our roles.
Please let us know your requirements early on so that we can make sure you have everything you need up front to help make the recruitment process and experience as easy as possible.
Finally, if you feel that you don’t meet all the criteria included above but have transferable skills and relevant experience.
ML Solutions Architect employer: Rowden Technologies
At Rowden, we pride ourselves on being an exceptional employer, fostering a culture of innovation and collaboration in our Bristol headquarters. Our commitment to flexible working arrangements, inclusive practices, and continuous employee development ensures that you can thrive both personally and professionally while contributing to critical national security projects. Join us to be part of a diverse team where your skills are valued, and your growth is supported in a dynamic and rewarding environment.
StudySmarter Expert Advice🤫
We think this is how you could land ML Solutions Architect
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Rowden Technologies or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to Rowden Technologies.
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like Rowden Technologies.
✨Explore Job Boards Specifically for Tech Roles
Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like Rowden Technologies that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace ML Solutions Architect
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Rowden Technologies.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Rowden Technologies and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at Rowden Technologies
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Rowden Technologies uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.