Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Technical Lead: Embedded Automotive Software

Cypher Consulting Europe
London
8 months ago
Applications closed

Related Jobs

View all jobs

Data analyst

Data Engineering Manager (Analytics Engineering and BI)

Data Engineering Manager (Analytics Engineering and BI)

Lead Underwriting Data Analyst (12 month FTC)

Data Analyst (Lead)

Lead Finance Data Analyst (12 month FTC)

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.

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.