At a Glance
- Tasks: Design and deploy cutting-edge ML solutions in high-performance engineering software.
- Company: Global leader in engineering simulation and modelling software.
- Benefits: Highly competitive salary, bonus, excellent benefits, and career development.
- Other info: Collaborate with talented engineers and shape the future of Applied AI.
- Why this job: Make a real impact on industry-leading software used by engineers worldwide.
- Qualifications: Strong C++ and Python skills with proven ML application experience.
The predicted salary is between 70000 - 90000 £ per year.
Location: Surrey, UK (Office-based)
The package: A highly competitive salary + Bonus + Excellent Benefits Package
Our client, a global leader in engineering simulation and modelling software, is significantly expanding its Applied AI capabilities. We are integrating machine learning and AI directly into our core high-performance engineering platforms used by engineers and scientists worldwide. This is a hands-on, senior-level role focused on designing, building, and deploying production-grade ML solutions within complex, performance-critical commercial software products — not research prototypes or isolated experiments.
The Role
As a Senior Machine Learning Software Engineer, you will play a key role in embedding intelligent capabilities into our flagship engineering tools. You will work at the intersection of advanced machine learning, high-performance software engineering, and domain-specific scientific computing. You will take ownership of ML initiatives from concept through to production deployment, ensuring models deliver measurable performance improvements while meeting strict engineering standards for reliability, efficiency, and scalability.
Key Responsibilities
- Design, implement, and deploy robust ML models into production engineering software systems
- Own the end-to-end ML lifecycle: data strategy, feature engineering, model development, optimisation, validation, and monitoring
- Translate complex scientific and engineering challenges into high-impact ML solutions
- Optimise models for speed, memory efficiency, and scalability in compute-intensive environments
- Write clean, efficient, testable, and maintainable production-quality code (primarily in C++ and Python)
- Integrate ML capabilities seamlessly into existing large-scale software architectures via APIs, libraries, and microservices
- Collaborate closely with software engineers, numerical analysts, and domain experts to deliver commercially valuable features
- Continuously improve model performance and robustness when working with real-world, noisy, or high-dimensional engineering data
Qualifications
- Strong commercial software engineering background with excellent C++ and Python skills
- Proven track record of successfully applying machine learning to real-world, complex problems in a production environment
- Significant experience developing and deploying ML models within large-scale software systems
- Deep understanding of model trade-offs (accuracy vs. speed vs. memory)
- Experience working with challenging, real-world datasets — including noisy, sparse, or domain-specific engineering data
- Strong ability to write high-quality, scalable, and production-ready code
- Hands-on expertise with modern ML frameworks (PyTorch, TensorFlow, or JAX)
- Background in scientific computing, numerical methods, finite element analysis, or optimisation techniques
- Experience with GPU acceleration (CUDA), parallel computing, or high-performance computing (HPC)
- Practical knowledge of MLOps, model serving, CI/CD for ML, and production deployment pipelines
- Experience integrating ML components into existing commercial C++ codebases
- Familiarity with engineering simulation, physics-based modelling, or CAE tools
The Great Aspects of this role
- Work on genuinely challenging technical problems where ML directly enhances industry-leading engineering software
- High degree of ownership and visible impact on products used globally
- Collaborate with talented, experienced engineers and subject matter experts
- Opportunity to shape how Applied AI is embedded into core commercial platforms for years to come
- Technically deep, long-horizon work — far from short-term experimental ML projects
- Excellent compensation, benefits, and career development opportunities
This is an outstanding opportunity for an experienced ML Software Engineer who enjoys solving hard engineering problems and delivering production AI capabilities that matter.
Senior Machine Learning Software Engineer (ML/AI) in Guildford employer: International Software Co
Join a global leader in engineering simulation and modelling software, where as a Senior Machine Learning Software Engineer, you will tackle complex challenges that directly enhance industry-leading products. Enjoy a collaborative work culture with a high degree of ownership, excellent compensation, and robust career development opportunities in the vibrant setting of Surrey, UK, making it an ideal place for those seeking meaningful and impactful employment.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Machine Learning Software Engineer (ML/AI) in Guildford
✨Join Local Tech Meetups
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✨Contribute to Open Source Projects
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We think you need these skills to ace Senior Machine Learning Software Engineer (ML/AI) in Guildford
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 International Software Co.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at International Software Co 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 International Software Co
✨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 International Software Co 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.