Technical Lead: Embedded Automotive Software

Cypher Consulting Europe
London
10 months ago
Applications closed

Related Jobs

View all jobs

Head of Data Science

Head of Data Science

Lead Data Scientist

Lead Machine Learning Engineer

Principal Machine Learning Engineer

Business Data Analyst

We are looking for a Technical Lead with strong expertise in automotive-grade embedded software development for high-performance, distributed computing systems. In this role, you will be part of an engineering team responsible for developing software solutions for edge devices, enabling large-scale data collection, experimentation, validation, and autonomy in a fleet of vehicles. You will design the software architecture to integrate machine learning-based autonomous driving (AD) solutions into L2-L3 automotive systems, ensuring high reliability, performance, and compliance with safety standards. This is a high-impact role that provides broad technical leadership within a fast-growing team.

Tasks

  • Technical Program Leadership:Lead key embedded software development projects, ensuring timely delivery by managing requirements, risks, milestones, and dependencies, with a strong emphasis on safety and compliance.
  • Software Architecture Design:Develop and implement software architectures to integrate ML-based AD solutions into L2-L3 automotive applications, ensuring seamless integration with OEM environments and sensor systems.
  • Collaborative Development:Work closely with machine learning engineers, software developers, system engineers, and product managers to refine the embedded software architecture.
  • Safety & Compliance:Ensure compliance with ISO 26262 functional safety standards, ASPICE processes, and other automotive safety regulations.
  • Code Base Management:Maintain a scalable, robust, and compliant embedded software codebase to support rapid development and future scalability.
  • Real-Time Systems Development:Design, develop, and maintain real-time applications for Linux-based and QNX-based embedded systems, focusing on data collection, storage, and edge-based machine learning inference.
  • Fault Tolerance & Diagnostics:Implement fault-tolerant software solutions with comprehensive diagnostics for real-time issue detection and resolution.
  • Mentorship & Leadership:Provide technical mentorship to engineers, lead design reviews, and foster a culture of engineering excellence within the team.

Requirements

  • Proven Experience:Extensive background in developing and deploying safety-critical automotive embedded software using C++.
  • Automotive Compliance:Strong understanding of ASPICE-compliant SDLC processes and ISO 26262 functional safety standards.
  • AUTOSAR Expertise:Experience in designing and implementing embedded software using the AUTOSAR architecture.
  • Technical Leadership:Demonstrated ability to lead large-scale technical programs and cross-functional teams.
  • Strong Communication:Ability to articulate complex technical and business concepts to both engineering and non-engineering stakeholders.
  • Educational Background:Bachelor’s degree in Computer Science, Electrical Engineering, or a related field (or equivalent professional experience).

Preferred Qualifications:

  • Programming Expertise:Proficiency in both C++ and Rust for embedded software development.
  • Advanced Degree:Master’s degree or higher in Computer Science, Electrical Engineering, or a related field.
  • Embedded Systems Experience:Strong background in developing software for Linux, QNX, or other automotive embedded operating systems.
  • Autonomous Driving Knowledge:Experience in L2-L3 ADAS applications and integrating ML-based AD solutions into automotive systems.

Work Location & Environment:

This is a full-time, London-based role with a hybrid working policy, offering flexibility between office collaboration and remote work



Cypher Consulting Europe takes pride in its ability to deliver expert consultants across a wide spectrum of technologies and industry sectors.

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 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.

Neurodiversity in Machine Learning Careers: Turning Different Thinking into a Superpower

Machine learning is about more than just models & metrics. It’s about spotting patterns others miss, asking better questions, challenging assumptions & building systems that work reliably in the real world. That makes it a natural home for many neurodivergent people. If you live with ADHD, autism or dyslexia, you may have been told your brain is “too distracted”, “too literal” or “too disorganised” for a technical career. In reality, many of the traits that can make school or traditional offices hard are exactly the traits that make for excellent ML engineers, applied scientists & MLOps specialists. This guide is written for neurodivergent ML job seekers in the UK. We’ll explore: What neurodiversity means in a machine learning context How ADHD, autism & dyslexia strengths map to ML roles Practical workplace adjustments you can ask for under UK law How to talk about neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in ML – & how to turn “different thinking” into a genuine career advantage.