National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Digital Design Chip Lead - (digital - AMS - SOC

IC Resources
London
2 months ago
Applications closed

Related Jobs

View all jobs

Senior Digital FPGA Engineer

Design Systems Analyst (Smart Places & Digital Twin Specialist)

Machine Learning Engineer

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Brand new, and cutting edge AI project, working for an exciting US start-up in the semiconductor space - to be based full-time within the UK.

Salary is negotiable - (based on seniority and relevance of experience) - circa £100-130k (or higher)

I am looking for a chip design lead to be responsible for the end to end design, set-up, micro-architecture definition, definition of the whole process & design flow and RTL design of a new AI project, based on neural networks technology.

You will be the lead designer, with duties including team leadership / management of a small team in charge of delivering the full chip to delivery at the fab.

Must have experience:

  • Degree / Masters / PhD in electronics / micro-electronics, physics or similar field
  • 10-20 years' experience of full chip design and delivery
  • Tech lead / team leadership / team management
  • Digital / AMS, analog-mixed-signal IP, chips and SOCs
  • ASIC & FPGA - verilog, system verilog, VHDL
  • ADC / DAC - digital - analog interfaces
  • Functional verification - system verilog - IP, system, sub-system, block, top level experience
  • Creation of test-benches
  • detailed knowledge of complex tape-out processes, and interactions with fabrication plants
  • Full digital design flow, from RTL2GDS
  • SOC design, integration, system design, system architecture
  • power management / PMIC / ultra-low power / optimisation & performance
  • synthesis / HLS / STA
  • physical implementation / physical design

Bonus / nice to have skills

  • CPU / GPU / RISC-V design and architecture
  • TPU / VPU / FPU - tensor, vector or floating point processor units
  • HW, hardware accelerators
  • PLLs / filter design
  • RF-SOC
  • DSP, signal processing
  • Flash memory - DDR / HBM / high-bandwith memory / cache chorency
  • clock, timing constraints

This position is ONLY available to senior level digital design engineers with full UK working rights

National AI Awards 2025

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.

Part-Time Study Routes That Lead to AI Jobs: Evening Courses, Bootcamps & Online Masters

Artificial intelligence (AI) is reshaping industries at an unprecedented pace. From automating mundane tasks in finance to driving innovation in healthcare diagnostics, the demand for AI-skilled professionals is skyrocketing. In the United Kingdom alone, AI is forecast to deliver over £400 billion to the economy by 2030 and generate millions of new jobs across sectors. Yet, for many ambitious professionals, taking time away from work to upskill can feel like an impossible ask. Thankfully, part-time learning options have proliferated: evening courses, intensive bootcamps and flexible online master’s programmes empower you to learn AI while working. This comprehensive guide explores every route—from short tasters to deep-dive MScs—showcasing providers, course formats, funding options and practical tips. Whether you’re a career changer, a busy manager or a self-taught developer keen to go further, you’ll discover a pathway to fit your schedule, budget and goals.

Top 10 Mistakes Candidates Make When Applying for AI Jobs—And How to Avoid Them

Avoid the biggest pitfalls when applying for artificial intelligence jobs. Discover the top 10 mistakes AI candidates make—plus expert tips and internal resources to land your dream role. Introduction The market for AI jobs in the UK is booming. From computer-vision start-ups in Cambridge to global fintechs in London searching for machine-learning engineers, demand for artificial-intelligence talent shows no sign of slowing. But while vacancies grow, so does the competition. Recruiters tell us they reject up to 75 per cent of applications before shortlisting—often for mistakes that could have been fixed in minutes. To help you stand out, we’ve analysed thousands of recent applications posted on ArtificialIntelligenceJobs.co.uk, spoken with in-house talent teams and independent recruiters, and distilled their feedback into a definitive “top mistakes” list. Below you’ll find the ten most common errors, along with actionable fixes, keyword-rich guidance and handy internal links to deeper resources on our site. Bookmark this page before you hit “Apply”—it could be the difference between the “reject” pile and a career-defining interview.