Go Engineer

Fynity
Nottingham
1 month ago
Applications closed

Related Jobs

View all jobs

Vision Systems Engineer

Automation Engineer

Senior Systems Engineer

Software Engineer

Data Engineer / Analytics Engineer

Data Engineer (Snowflake) - Grade D

Go Engineer


Are you an experienced Go Engineer looking for your next challenge? Do you thrive in a collaborative, forward-thinking environment where your technical expertise can make a real impact? If so, we want to hear from you!


We’re seeking a Go Engineer to join our high-performing team, where you’ll play a pivotal role in designing, developing, and optimising innovative software solutions. You’ll work closely with Product, Architecture, and Principal Engineers to deliver robust, scalable applications while mentoring and guiding junior engineers.


What You’ll Do:

  • Design and implement high-quality, scalable software solutions in Go.
  • Work across all stages of the software development lifecycle, from concept to deployment and maintenance.
  • Collaborate with cross-functional teams to define and deliver technical solutions.
  • Optimise performance, resolve technical issues, and enhance existing systems.
  • Guide and mentor Junior Engineers, sharing best practices and knowledge.
  • Stay ahead of the curve by exploring new technologies and methodologies.
  • Maintain technical documentation and contribute to continuous improvement.



What We’re Looking For:

Essential:

  • Extensive experience with Golang, including frameworks like Echo, Gin, or Gorilla Mux.
  • A strong understanding of software development best practices, including CI/CD, TDD, and scalable microservices architecture.
  • Solid knowledge of machine learning techniques to enhance search capabilities.
  • Experience working in Agile environments.
  • Any knowledge of Python, Rust, PHP, or Perl is highly beneficial.
  • Excellent communication and leadership skills.



What’s in it for you?

  • Competitive salary (£60,000 - £65,000) depending on experience.
  • Remote working (2 days a quarter in the office in fleet)
  • Be part of a collaborative, innovative, and diverse team.
  • Opportunity to work on cutting-edge projects that drive real value.
  • Support for professional growth, mentorship, and learning opportunities.
  • A culture that values inclusion, flexibility, and work-life balance.


If you’re passionate about software engineering and eager to make a difference, apply today!

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.

Machine Learning Jobs at Newly Funded UK Start-ups: Q3 2025 Investment Tracker

Machine learning (ML) has become the beating heart of modern tech innovation, powering breakthroughs in healthcare, finance, cybersecurity, robotics, and more. Across the United Kingdom, this surge in ML-driven solutions is fueling the success of countless start-ups—and spurring demand for talented machine learning engineers, data scientists, and related professionals. If you’re eager to join a high-growth ML company or simply want to keep tabs on the latest trends, this Q3 2025 Investment Tracker will guide you through the newly funded UK start-ups pushing the boundaries of ML. In this article, we’ll highlight key developments from Q3 2025, delve into the most promising newly funded ventures, and shed light on the machine learning roles they’re urgently seeking to fill. Plus, we’ll show you how to connect with these employers via MachineLearningJobs.co.uk, a dedicated platform for ML job seekers. Let’s dive in!

Portfolio Projects That Get You Hired for Machine Learning Jobs (With Real GitHub Examples)

In today’s data-driven landscape, the field of machine learning (ML) is one of the most sought-after career paths. From startups to multinational enterprises, organisations are on the lookout for professionals who can develop and deploy ML models that drive impactful decisions. Whether you’re an aspiring data scientist, a seasoned researcher, or a machine learning engineer, one element can truly make your CV shine: a compelling portfolio. While your CV and cover letter detail your educational background and professional experiences, a portfolio reveals your practical know-how. The code you share, the projects you build, and your problem-solving process all help prospective employers ascertain if you’re the right fit for their team. But what kinds of portfolio projects stand out, and how can you showcase them effectively? This article provides the answers. We’ll look at: Why a machine learning portfolio is critical for impressing recruiters. How to select appropriate ML projects for your target roles. Inspirational GitHub examples that exemplify strong project structure and presentation. Tangible project ideas you can start immediately, from predictive modelling to computer vision. Best practices for showcasing your work on GitHub, personal websites, and beyond. Finally, we’ll share how you can leverage these projects to unlock opportunities—plus a handy link to upload your CV on Machine Learning Jobs when you’re ready to apply. Get ready to build a portfolio that underscores your skill set and positions you for the ML role you’ve been dreaming of!

Machine Learning Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Machine learning is fuelling innovation across every industry, from healthcare to retail to financial services. As organisations look to harness large datasets and predictive algorithms to gain competitive advantages, the demand for skilled ML professionals continues to soar. Whether you’re aiming for a machine learning engineer role or a research scientist position, strong interview performance can open doors to dynamic projects and fulfilling careers. However, machine learning interviews differ from standard software engineering ones. Beyond coding proficiency, you’ll be tested on algorithms, mathematics, data manipulation, and applied problem-solving skills. Employers also expect you to discuss how to deploy models in production and maintain them effectively—touching on MLOps or advanced system design for scaling model inferences. In this guide, we’ve compiled 30 real coding & system‑design questions you might face in a machine learning job interview. From linear regression to distributed training strategies, these questions aim to test your depth of knowledge and practical know‑how. And if you’re ready to find your next ML opportunity in the UK, head to www.machinelearningjobs.co.uk—a prime location for the latest machine learning vacancies. Let’s dive in and gear up for success in your forthcoming interviews.