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- Tasks: Develop intelligent test frameworks and optimisation algorithms for optical network systems.
- Company: Join a leading tech company at the forefront of optical networking.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Why this job: Make a real impact by optimising cutting-edge technology in a collaborative environment.
- Qualifications: Proficiency in Python, C++, or C# and experience with optimisation algorithms.
- Other info: Dynamic team culture with excellent career advancement opportunities.
The predicted salary is between 36000 - 60000 £ per year.
We are looking for a Systems Optimisation Engineer to develop intelligent test frameworks and optimisation algorithms for optical network systems. This cross-disciplinary role blends software engineering, algorithm development, and hardware test integration to reduce test time, improve throughput, and enhance performance analysis. You will collaborate closely with hardware test engineers to refine burst-mode test strategies, optimise equalisation parameters, and accelerate product evaluation from R&D through production.
Responsibilities
- Join the Optical Network Integration team and collaborate closely with other teams.
- Design and implement automated test frameworks for high-speed optical network systems, integrating hardware instrumentation (oscilloscopes, BERTs, burst-mode testers).
- Develop metaheuristic and data-driven optimisation algorithms (e.g., genetic algorithms, simulated annealing, swarm optimisation) to reduce test time and improve measurement efficiency.
- Work with hardware engineers to optimise burst-mode test sequences, equalisation settings (CTLE, FFE, DFE), and link tuning strategies.
- Analyse large datasets from validation and production testing to identify performance trends, bottlenecks, and opportunities for improvement.
- Implement adaptive, hardware-aware test routines that adjust dynamically based on device behaviour.
- Support the integration of optimised test flows into high-volume manufacturing environments.
- Maintain scalable, modular software architectures for future test platforms.
Skills & Experience
- Proficiency in software development for test automation (Python, C++, or C#).
- Experience with metaheuristic optimisation (e.g., GA, simulated annealing, particle swarm).
- Experience with AI/ML techniques (e.g., reinforcement learning, predictive modelling) for test optimisation.
- Collaborative mindset to work closely with hardware engineers and manufacturing teams.
- Familiarity with production test time optimisation in semiconductor or optical device environments.
- Exposure to cloud-based data pipelines for large-scale test data processing.
- Degree in Computer Science, Electrical/Electronic Engineering, Applied Mathematics, or related field.
Systems Optimisation Engineer in London employer: Oriole
Contact Detail:
Oriole Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Systems Optimisation Engineer in London
✨Tip Number 1
Network like a pro! Reach out to professionals in the optical network field on LinkedIn or at industry events. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects related to test automation and optimisation algorithms. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice explaining your past projects and how they relate to the role of Systems Optimisation Engineer.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Systems Optimisation Engineer in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Systems Optimisation Engineer role. Highlight your experience with software development, optimisation algorithms, and any relevant projects that showcase your skills in test automation and data analysis.
Craft a Compelling Cover Letter: Your cover letter should tell us why you're the perfect fit for this role. Share specific examples of how you've collaborated with hardware engineers or developed optimisation algorithms in the past. Make it personal and engaging!
Showcase Relevant Skills: Don’t forget to emphasise your proficiency in programming languages like Python, C++, or C#. If you have experience with AI/ML techniques or cloud-based data processing, make sure to mention that too!
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It’s the best way for us to receive your application and get to know you better. We can’t wait to see what you bring to the table!
How to prepare for a job interview at Oriole
✨Know Your Algorithms
Brush up on your knowledge of metaheuristic optimisation algorithms like genetic algorithms and simulated annealing. Be ready to discuss how you've applied these techniques in past projects, as this will show your practical understanding and ability to contribute to the role.
✨Showcase Your Coding Skills
Since proficiency in Python, C++, or C# is crucial, prepare to demonstrate your coding skills. You might be asked to solve a problem on the spot, so practice coding challenges related to test automation and be ready to explain your thought process.
✨Collaborate Like a Pro
This role requires a collaborative mindset, so think of examples where you've successfully worked with hardware engineers or cross-functional teams. Highlight your communication skills and how you’ve contributed to optimising test strategies in previous roles.
✨Data Analysis is Key
Familiarise yourself with analysing large datasets and identifying performance trends. Be prepared to discuss any experience you have with data-driven decision-making and how it has led to improvements in test efficiency or product evaluation.
