Optical Software Engineer

BREAM & LAANAIA
Birmingham
1 week ago
Create job alert

JOB SUMMARY


For over three decades, our client, based in Silicon Valley, California and with global locations around the world has solved semiconductor design challenges by offering affordable and competitive TCAD (Technology Computer Aided Design) and EDA (Electronic Design Automation) softwares, proven design IP (intellectual property), and world class support to engineers and researchers across the globe.


Their solutions span from atoms to systems: starting with simulation of material behavior impacting semiconductor devices, to design of transistor circuits and IP blocks for systems-on-chip (SoC).


We are looking for anOptical Software Engineer.


What you will be doing

As a member of the TCAD group, you will design, implement, evaluate, and improve physical models and optical methods for the simulation of electro-optical semiconductor devices. The successful candidate will be an experienced software engineer with expertise in simulating optical devices such as lasers, LEDs, displays, or sensors.


Essential job functions and responsibilities

  • Develop, support, test, and maintain existing optical simulation software
  • Identify, implement, and test new optical solvers (such as DGTD) and physical models.
  • Provide accurate and effective written documentation.
  • Communicate complex ideas and testing results effectively, both orally and in writing.


Education level

Ph,D. in Physics, Engineering, Computational Science, or a related field


Hard skills

  • Knowledge of quantum mechanics and light-matter interaction.
  • Strong electro-optics fundamentals including solid-state physics, optical physics, and optical solution methods.
  • Experience with laser, LED, display, or sensor simulation.
  • Experience implementing optical methods such as raytracing, finite difference time domain (FDTD), beam propagation method (BPM), or mode solvers.
  • Proficiency in Matlab, C ++, Python and software design
  • Experience with parallel computing.


Soft skills

  • Natural team player who works well in international and remote team.
  • Strong written and verbal communication and interpersonal skills.
  • Creative problem-solving skills.
  • Good organization, time management, and task prioritization skills.


Location

Cambridge, UK (On site/Hybrid/Remote)

Locations in Grenoble, France or Vienna, Austria (On site/Hybrid/Remote) can also be considered


Why join the team?

If you are looking to give more essence to what you are doing, while developing advanced softwares for the A players of the semiconductor industry , you should be applying for this job. If you are looking to join an international team of highly trained and experienced engineers working on new numerical solvers and techniques; you've found the right place!


Please Note : Sponsorship not available for this position.

Please send your application to Bream & Laanaia, the high tech recruitment experts:

Related Jobs

View all jobs

Optical Software Engineer

Optical Software Engineer

Optical Software Engineer

Senior System Engineer

Senior Applied Scientist, Causal Inference, EU AVS/VX BIE team

Principal Structural Engineer

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Careers

Tips for Staying Inspired: How Machine Learning Pros Fuel Creativity and Innovation

Machine learning (ML) continues to reshape industries—from personalised e-commerce recommendations and autonomous vehicles to advanced healthcare diagnostics and predictive maintenance in manufacturing. Yet behind every revolutionary model lies a challenging and sometimes repetitive process: data cleaning, hyperparameter tuning, infrastructure management, stakeholder communications, and constant performance monitoring. It’s no wonder many ML professionals can experience creative fatigue or get stuck in the daily grind. So, how do machine learning experts keep their spark alive and continually generate fresh ideas? Below, you’ll find ten actionable strategies that successful ML engineers, data scientists, and research scientists use to stay innovative and push boundaries. Whether you’re an experienced practitioner or just breaking into the field, these tips can help you fuel creativity and discover new angles for solving complex problems.

Careers

Top 10 Machine Learning Career Myths Debunked: Key Facts for Aspiring Professionals

Machine learning (ML) has become one of the hottest fields in technology—touching everything from recommendation engines and self-driving cars to language translation and healthcare diagnostics. The immense potential of ML, combined with attractive compensation packages and high-profile success stories, has spurred countless professionals and students to explore this career path. Yet, despite the boom in demand and innovation, machine learning is not exempt from myths and misconceptions. At MachineLearningJobs.co.uk, we’ve had front-row seats to the real-life career journeys and hiring needs in this field. We see, time and again, that outdated assumptions—like needing a PhD from a top university or that ML is purely about deep neural networks—can mislead new entrants and even deter seasoned professionals from making a successful transition. If you’re curious about a career in machine learning or looking to take your existing ML expertise to the next level, this article is for you. Below, we debunk 10 of the most persistent myths about machine learning careers and offer a clear-eyed view of the essential skills, opportunities, and realistic paths forward. By the end, you’ll be better equipped to make informed decisions about your future in this dynamic and rewarding domain.

Careers

Global vs. Local: Comparing the UK Machine Learning Job Market to International Landscapes

How to evaluate opportunities, salaries, and work culture in machine learning across the UK, the US, Europe, and Asia Machine learning (ML) has rapidly transcended the research labs of academia to become a foundational pillar of modern technology. From recommendation engines and autonomous vehicles to fraud detection and personalised healthcare, machine learning techniques are increasingly ubiquitous, transforming how organisations operate. This surge in applications has fuelled an extraordinary global demand for ML professionals—data scientists, ML engineers, research scientists, and more. In this article, we’ll examine how the UK machine learning job market compares to prominent international hubs, including the United States, Europe, and Asia. We’ll explore hiring trends, salary ranges, workplace cultures, and the nuances of remote and overseas roles. Whether you’re a fresh graduate aiming to break into the field, a software engineer with an ML specialisation, or a seasoned professional seeking your next challenge, understanding the global ML landscape is essential for making an informed career move. By the end of this overview, you’ll be equipped with insights into which regions offer the best blend of salaries, work-life balance, and cutting-edge projects—plus practical tips on how to succeed in a domain that’s constantly evolving. Let’s dive in.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.