Software Engineer - C# / Design and Simulation

Yarnton
2 days ago
Create job alert

Software Engineer – AI & Simulation

🚀 Redefine Possibilities. Engineer the Future. Make Your Mark.

Looking for an easy, predictable role? This isn’t it. Looking for an opportunity to push limits, tackle real-world technical challenges, and be part of something ground breaking? Keep reading.

We’re talking about cutting-edge software, AI-driven simulation, advancing the boundaries of engineering.

This is a role for someone who thrives on solving complex problems, working alongside top-tier technical minds, and seeing their ideas turn into real-world impact.

đź’ˇ Why this role will excite you:

  • Work at the intersection of AI, simulation, and next-gen engineering.

  • Be part of a high-performance team developing software that transforms industries.

  • Get involved in every stage of the development cycle, from concept to implementation.

  • A place where initiative isn’t just welcomed—it’s essential.

  • Fast-paced, ever-evolving, and built for those who love a challenge.

    🛠 What you’ll be doing:

  • Designing and developing cutting-edge software for next-generation industrial applications.

  • Building intelligent algorithms that optimize complex engineering processes.

  • Creating visualization tools that bring raw data to life.

  • Working side by side with specialists in engineering, data science, and physics to push technological boundaries.

    âś… What makes you a great fit:

  • A top academic record in a STEM subject—you're no stranger to complex problem-solving.

  • A strong grasp of coding principles and software architecture.

  • Proficiency in C# and C++/Python

  • A natural problem-solver with a passion for tech-driven innovation.

  • Someone who doesn’t wait to be told what to do—proactivity is key.

    Humand Talent Solutions and their clients and associates do not discriminate on any of the following and any terminology that suggests that should be made aware to our business ASAP.

    Categories include:

  • gender

  • race

  • religion or belief

  • disability

  • age

  • pregnancy and maternity

  • marriage and civil partnership

  • sexual orientation

  • gender reassignment

Related Jobs

View all jobs

Software Engineer

Software Engineer - C# / Design and Simulation

Software Engineers

Software Team Manchester

Java Software Engineer (SC cleared)

Java Software Engineer (SC cleared)

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.

Tips for Staying Inspired: How Data Science Pros Fuel Creativity and Innovation

Data science sits at the dynamic intersection of statistics, computer science, and domain expertise, driving powerful innovations in industries ranging from healthcare to finance, and from retail to robotics. Yet, the daily reality for many data scientists can be a far cry from starry-eyed talk of AI and machine learning transformations. Instead, it often involves endless data wrangling, model tuning, and scrutiny over metrics. Maintaining a sense of creativity in this environment can be an uphill battle. So, how do successful data scientists continue to dream big and innovate, even when dealing with the nitty-gritty of data pipelines, debugging code, or explaining results to stakeholders? Below, we outline ten practical strategies to help data analysts, machine learning engineers, and research scientists stay inspired and push their ideas further. Whether you’re just starting out or looking to reinvigorate a long-standing career, these pointers can help you find fresh sparks of motivation.

Top 10 Data Science Career Myths Debunked: Key Facts for Aspiring Professionals

Data science has become one of the most sought-after fields in the tech world, promising attractive salaries, cutting-edge projects, and the opportunity to shape decision-making in virtually every industry. From e-commerce recommendation engines to AI-powered medical diagnostics, data scientists are the force behind innovations that drive productivity and improve people’s lives. Yet, despite the demand and glamour often associated with this discipline, data science is also shrouded in misconceptions. Some believe you need a PhD in mathematics or statistics; others assume data science is exclusively about machine learning or coding. At DataScience-Jobs.co.uk, we’ve encountered a wide array of myths that can discourage talented individuals or mislead those exploring a data science career. This article aims to bust the top 10 data science career myths—providing clarity on what data scientists actually do and illuminating the true diversity and inclusiveness of this exciting field. Whether you’re a recent graduate, a professional looking to pivot, or simply curious about data science, read on to discover the reality behind the myths.

Global vs. Local: Comparing the UK Data Science Job Market to International Landscapes

How to evaluate salaries, opportunities, and work culture in data science across the UK, the US, Europe, and Asia Data science has proven to be more than a passing trend; it is now a foundational pillar of modern decision-making in virtually every industry—from healthcare and finance to retail and entertainment. As the volume of data grows exponentially, organisations urgently need professionals who can transform raw information into actionable insights. This high demand has sparked a wave of new opportunities for data scientists worldwide. In this article, we’ll compare the UK data science job market to those in the United States, Europe, and Asia. We’ll explore hiring trends, salary benchmarks, and cultural nuances to help you decide whether to focus your career locally or consider opportunities overseas or in fully remote roles. Whether you’re a fresh graduate looking for your first data science position, an experienced data professional pivoting from analytics, or a software engineer eager to break into machine learning, understanding the global data science landscape can be a game-changer. By the end of this overview, you’ll be better equipped to navigate the expanding world of data science—knowing which skills and certifications matter most, how salaries differ between regions, and what to expect from distinct work cultures. Let’s dive in.