Cnc Programmer

Shipton On Cherwell
1 year ago
Applications closed

CNC Programmer
Company overview Alloyed is a young venture-funded company of around 120 world-class metallurgists, mechanical engineers, technicians, and software developers working across three offices in the UK and one in the US, building the future of advanced metal components. We use proprietary software packages which combine advanced machine learning and physical modelling, as well as extensive experimental facilities, to 3D print metal components better and faster than anyone else.
The CNC Programmer will be responsible for the programming, setup, and operation of CNC machines to produce high-quality, high-precision parts for new product introduction (NPI). The ideal candidate should have a strong background in CNC programming and operation, as well as a keen eye for detail and a commitment to maintaining the highest standards of quality and precision. The ideal candidate will also have some experience with Design for Manufacturing (DFM) and will be skilled with CAD to design and propose fixturing and component design that aid its manufacturability for high-precision CNC results. You will be based at Abingdon Business Park, south of Oxford. Training will be provided where required.
Cnc Programmer Responsibilities:
Programming:

  • Develop 5-axis CNC programs for new product introductions based on engineering drawings, models, and specifications.
  • Optimise programs to ensure efficient production, minimise waste, and reduce cycle times.
    CNC Machine Setup and Operation:
  • Set up CNC machines, including loading materials, tooling selection, and fixture installation.
  • Perform routine maintenance and troubleshooting on CNC machines to ensure optimal performance.
  • Operate CNC machines to manufacture parts according to established specifications and quality standards.
    New Product Introduction (NPI):
  • Collaborate with the engineering and design teams during the NPI process to provide technical expertise and insights.
  • Review engineering drawings and models to identify potential manufacturing challenges and offer design for manufacturability (DFM) recommendations.
  • Participate in prototype development, ensuring accurate translation of designs into functional parts
    Quality Assurance and Documentation:
  • Monitor and maintain quality control procedures, including in-process inspections and final product verification.
  • Document all relevant data, including measurements, process parameters, and any deviations or nonconformances.
    Essential
  • Experience in 5-axis programming with Fusion 360 CAM
  • Jig and fixture design and Fusion 360 CAD
  • Working in a precision engineering environment • Organised and able to work independently, but also to collaborate with a diverse, fast-moving team
  • Proficient with Microsoft Office (Excel, PowerPoint, Outlook)
  • Hands-on attitude and willingness to learn new skills
  • High level of attention to detail
    Desirable
  • Experience with DMG milling machine and Siemens control
  • Lathe programming and operation
  • Understanding of DFM for additively manufactured near net-shape parts
  • Experience operating under AS9100/ISO9001 environment
  • New product introduction – FAI, AQPQ
  • Willingness to work flexible hours if needed
    The supporting statement should explain your motivations and how you meet the selection criteria for the role using examples of your skills and any experience. All documents should be uploaded as PDF files with your name and document type in the filename. Please provide details of two referees and indicate if we can contact them now

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.

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.