At a Glance
- Tasks: Design and build scalable backend systems and machine learning infrastructure.
- Company: Join a venture-backed tech company solving complex challenges in natural resources.
- Benefits: Competitive salary, equity package, and significant influence over technical direction.
- Other info: Work in a fast-paced startup with excellent career growth opportunities.
- Why this job: Make a real impact on cutting-edge AI and data-driven products.
- Qualifications: 5+ years in software systems, strong Python skills, and cloud expertise.
The predicted salary is between 60000 - 80000 £ per year.
We're working with a venture backed technology company that is building software to solve complex challenges within the natural resources sector. Following recent funding and growing customer demand, they are looking to hire a Backend Engineer with strong MLOps and cloud engineering expertise to help scale their platform, machine learning infrastructure, and data capabilities.
This is an opportunity to join a small, high performing team where you'll have significant ownership over technical decisions, architecture, and the systems that underpin cutting edge AI and data driven products.
The Role
The successful candidate will play a key role in designing, building, and operating the backend systems, machine learning infrastructure, and cloud platforms that power the company's products.
Key responsibilities include:
- Designing and building scalable backend services, APIs, and distributed systems using Python
- Developing and maintaining production grade machine learning workflows and data pipelines
- Building infrastructure to support model training, deployment, monitoring, and lifecycle management
- Managing and improving cloud infrastructure, primarily within Azure
- Working closely with Data Scientists to productionise machine learning models and AI driven products
- Implementing MLOps best practices, including automated testing, deployment, monitoring, and observability
- Designing robust data ingestion and processing pipelines for large and complex datasets
- Improving platform reliability, scalability, and performance across backend and ML systems
- Driving engineering best practices around architecture, CI/CD, infrastructure as code, and deployment workflows
- Taking ownership of projects from concept through to production deployment
Requirements
- 5+ years of experience building and operating production software systems
- Strong software engineering experience with Python
- Experience building and maintaining machine learning workflows or MLOps platforms
- Strong understanding of cloud infrastructure, preferably Azure
- Experience with containerisation and orchestration technologies such as Docker and Kubernetes
- Experience building APIs, backend services, and distributed systems
- Strong understanding of modern software architecture and engineering best practices
- Experience working with data intensive applications, ETL pipelines, or large scale datasets
- Familiarity with CI/CD pipelines and infrastructure as code
- Strong organisational skills and ability to prioritise effectively
- Comfortable working in a fast moving startup environment
- Proactive mindset with a desire to improve systems, processes, and products
Desirable Experience
- Experience deploying and operating machine learning models in production
- Experience with ML orchestration tools such as Airflow, Prefect, Kubeflow, MLflow, or similar
- Exposure to geospatial data, scientific computing, environmental modelling, or natural resources applications
- Experience with observability, monitoring, and platform engineering practices
- Experience working with LLMs, AI systems, or modern machine learning frameworks
- Strong DevOps and Site Reliability Engineering experience
- Experience working within venture backed startups or scale ups
What's on Offer
- Opportunity to join a well funded, high growth technology business
- Significant influence over technical direction, platform architecture, and ML infrastructure strategy
- Work alongside experienced engineers, researchers, data scientists, and domain experts
- Exposure to cutting edge applications of AI, machine learning, and scientific data
- Competitive salary and equity package
Backend Engineer in City of London employer: Explore Group
Join a dynamic and innovative venture-backed technology company that is at the forefront of solving complex challenges in the natural resources sector. As a Backend Engineer, you will enjoy a collaborative work culture that fosters significant ownership over technical decisions and offers ample opportunities for professional growth, all while working with cutting-edge AI and data-driven products. With competitive salaries, equity packages, and the chance to influence the technical direction of a high-growth startup, this role promises a rewarding and meaningful career path.
StudySmarter Expert Advice🤫
We think this is how you could land Backend Engineer in City of London
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Explore Group!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Backend Engineer at Explore Group.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Explore Group.
✨Apply Directly through Our Website
When you find a suitable opening like Backend Engineer at Explore Group, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Backend Engineer in City of London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Explore Group, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Explore Group. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Explore Group
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Explore Group!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
