Full Stack Engineer

Haystack
Newcastle upon Tyne
1 year ago
Applications closed

Related Jobs

View all jobs

AI/ML Enterprise Architect - Cloud & MLOps Leader

Full Stack Data Engineer

Cloud Data Engineer & Full-Stack Platform Developer

Full Stack Developer - Data Engineering & GenAI Applications

Full-Stack Data Analyst: SQL, Dashboards & Insights

Data Scientist (Full Stack)

Senior .NET Developer


About Us

We are on a mission to accelerate home decarbonisation by making it easy for anyone to start that journey today. We help households implement the most impactful energy and carbon-saving measures within their budgets and circumstances.


We’ve developed a comprehensive technology platform that simplifies the entire domestic heating electrification lifecycle, from decision-making to installation and ongoing monitoring. Our tech stack includes machine learning tools for analyzing energy tariffs, LiDAR for home scanning, and generative AI for installation tooling—offering an exciting array of technologies for you to work on.


As a Seed-stage company with institutional backing, we have ambitious growth plans and the necessary funding to achieve them. Join our small but expanding team to help shape our core platform technologies.


Your Role

Our core platform services are crucial in integrating householder and installer experiences. Your responsibilities will include:

  • Understanding core heating system and physics concepts underpinning our modeling.
  • Designing, developing, and maintaining our core platform services, including APIs, workflows, and data pipelines.
  • Supporting front-end teams with UI product integration.
  • Assisting product owners by providing technical insights during requirement refinement.
  • Supporting existing applications in production.
  • Collaborating with team members through peer review.


What We’re Looking For

You are motivated by our mission to reduce household energy consumption and carbon emissions, with a keen interest in heating systems and energy technologies.


Communication and Interaction

  • Excellent communicator with strong spoken and written English skills.
  • Attention to detail.
  • Experience working well within a hybrid/remote team environment.


Technical Skills

  • Proven experience in designing, implementing, and deploying .NET Core solutions (Web API, MVC) and delivering full-stack solutions, including web interfaces.
  • Strong experience with application security best practices.
  • Familiarity with OAuth/OpenID patterns for authentication and authorization.
  • Experience troubleshooting complex .NET solutions in production environments.
  • Broad knowledge of application infrastructure concepts like DNS, networks, and connectivity issues.
  • Experience with Azure infrastructure, topology, and deployment.
  • Experience collaborating with product owners to resolve design conflicts.
  • Proven track record of learning new skills and technologies.
  • Strong background in math/physics or other sciences equivalent to A-level.


Technologies/Skills

  • Required:C#, .NET Core, Entity Framework, Git/GitHub Workflow, Azure Application Deployment, OAuth2/OpenID, MSSQL.
  • Desirable:Mass Transit, Docker, Content Management, Azure Infrastructure Management, Azure Functions, ARM/Terraform, JavaScript, MySQL.
  • Bonus:Experience in training/refining GPT models, Google Analytics Configuration.


What You Can Expect From Us

  • Impactful work towards net-zero carbon emissions.
  • Autonomy in shaping core platform technologies.
  • Backed by institutional funding with ambitious growth plans.
  • Exposure to a range of cutting-edge technologies.
  • Collaboration with a talented and supportive team.


Interview Process

We prioritise hiring and want to ensure mutual compatibility. Our process includes:

  • Initial introductory call from a hiring manager.
  • Time-constrained technical task for shortlisted candidates.
  • Technical interview with a team member.
  • Final culture fit interview with a senior leader.

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

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 for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Are you considering a career change into machine learning in your 30s, 40s or 50s? You’re not alone. In the UK, organisations across industries such as finance, healthcare, retail, government & technology are investing in machine learning to improve decisions, automate processes & unlock new insights. But with all the hype, it can be hard to tell which roles are real job opportunities and which are just buzzwords. This article gives you a practical, UK-focused reality check: which machine learning roles truly exist, what skills employers really hire for, how long retraining realistically takes, how to position your experience and whether age matters in your favour or not. Whether you come from analytics, engineering, operations, research, compliance or business strategy, there is a credible route into machine learning if you approach it strategically.

How to Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.

Maths for Machine Learning Jobs: The Only Topics You Actually Need (& How to Learn Them)

Machine learning job adverts in the UK love vague phrases like “strong maths” or “solid fundamentals”. That can make the whole field feel gatekept especially if you are a career changer or a student who has not touched maths since A level. Here is the practical truth. For most roles on MachineLearningJobs.co.uk such as Machine Learning Engineer, Applied Scientist, Data Scientist, NLP Engineer, Computer Vision Engineer or MLOps Engineer with modelling responsibilities the maths you actually use is concentrated in four areas: Linear algebra essentials (vectors, matrices, projections, PCA intuition) Probability & statistics (uncertainty, metrics, sampling, base rates) Calculus essentials (derivatives, chain rule, gradients, backprop intuition) Basic optimisation (loss functions, gradient descent, regularisation, tuning) If you can do those four things well you can build models, debug training, evaluate properly, explain trade-offs & sound credible in interviews. This guide gives you a clear scope plus a six-week learning plan, portfolio projects & resources so you can learn with momentum rather than drowning in theory.