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

Nominate & Attend

SG Technology | Lead Machine Learning Engineer

SG Technology
London
6 months ago
Applications closed

Related Jobs

View all jobs

Shift QC Analyst

Our client, a pioneering company in autonomous vehicle technology, is seeking an accomplished Technical Lead for Embedded Automotive Software to join their onboard Software Platform team. This role demands a seasoned leader with extensive experience in developing high-performance, reliable automotive-grade software for distributed, edge computing devices. As a pivotal member of the team, the Technical Lead will design and implement software architectures to integrate machine learning-based autonomous driving (AD) solutions into an automotive L2-L3 system application. This high-impact role offers visibility across the organisation and provides technical leadership for a rapidly growing team.
The Technical Lead will drive the development and deployment of embedded software that powers advanced AI models for autonomous driving, managing complex technical programs and ensuring the resilience, compliance, and performance of embedded automotive systems. This position requires close collaboration with diverse teams and leadership in achieving key program milestones within the autonomous driving domain.
Key Responsibilities

  • Technical Program Leadership:Independently lead large-scale areas of embedded software development, ensuring timely delivery by effectively managing requirements, risks, development strategies, milestones, and dependencies, with a critical focus on safety and compliance.
  • Software Architecture Design:Design and build software architectures to integrate machine learning-based autonomous driving solutions into L2-L3 automotive systems. Ensure integration with OEM software to facilitate full sensor integration and high-quality data capture for fully autonomous applications.
  • Collaborative Development:Collaborate with cross-functional teams, including machine learning engineers, software developers, systems engineers, and product managers, to refine and enhance the software architecture.
  • Compliance and Safety: Work closely with safety and functional safety teams to ensure adherence to ISO 26262 standards and other regulatory requirements, supporting ASPICE-compliant processes.
  • Code Base Management:Maintain a robust, scalable code base for embedded systems to support efficient development and future scalability.
  • Real-Time System Management:Develop and maintain real-time Linux- and QNX-based applications for embedded automotive devices, enabling data collection, storage, and machine learning inference at the edge.
  • Fault Tolerance and Diagnostics:Create fault-tolerant software with comprehensive diagnostic capabilities to ensure swift issue identification and resolution in deployed automotive systems.
  • Mentorship and Cultural Development:Mentor engineers and lead design reviews and architecture discussions to foster a culture of technical excellence, safety, and compliance.

Essential Qualifications

  • Extensive experience in developing safety-critical automotive embedded software in C++ with a track record of successfully leading large technical programs and teams.
  • Deep understanding of ASPICE-compliant Software Development Life Cycle (SDLC) processes.
  • Expertise in building embedded software using the AUTOSAR architecture.
  • Strong leadership abilities with experience in leading cross-functional teams and engaging stakeholders across divisions.
  • Exceptional communication skills, capable of clearly conveying complex technical and business concepts.
  • Bachelors degree in Computer Science, Electrical Engineering, or a related field, or equivalent professional experience.


Desirable Qualifications

  • Proficiency in both C++ and Rust for embedded software development.
  • A Masters degree or higher in Computer Science, Electrical Engineering, or a related field.
  • Experience developing software for diverse automotive embedded systems and operating systems, especially Linux and QNX.
  • Background in L2-L3 autonomous driving applications and integrating ML-based AD solutions within automotive environments.
  • Familiarity with ISO 26262 functional safety standards.


This is a full-time, London-based role with a hybrid working model to foster innovation and collaboration. With core working hours, the team can determine a schedule that balances office presence and remote work. This is an exciting opportunity to lead and shape the future of autonomous driving technology in a fast-paced, innovation-driven environment.

JBRP1_UKTJ

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.

How to Present Data Science Solutions to Non-Technical Audiences: A Public Speaking Guide for Job Seekers

The ability to communicate clearly is now just as important as knowing how to build a predictive model or fine-tune a neural network. In fact, many UK data science job interviews are now designed to test your ability to explain your work to non-technical audiences—not just your technical competence. Whether you’re applying for your first data science role or moving into a lead or consultancy position, this guide will show you how to structure your presentation, simplify technical content, design effective visuals, and confidently answer stakeholder questions.

Data Science Jobs UK 2025: 50 Companies Hiring Now

Bookmark this guide—refreshed every quarter—so you always know who’s really expanding their data‑science teams. Budgets for predictive analytics, GenAI pilots & real‑time decision engines keep climbing in 2025. The UK’s National AI Strategy, tax relief for R&D & a sharp rise in cloud adoption mean employers need applied scientists, ML engineers, experiment designers, causal‑inference specialists & analytics leaders—right now. Below you’ll find 50 organisations that have advertised UK‑based data‑science vacancies or announced head‑count growth during the past eight weeks. They’re grouped into five quick‑scan categories so you can jump straight to the kind of employer—& culture—that suits you. For every company you’ll see: Main UK hub Example live or recent vacancy Why it’s worth a look (tech stack, mission, culture) Search any employer on DataScience‑Jobs.co.uk to view current ads, or set up a free alert so fresh openings land straight in your inbox.

Return-to-Work Pathways: Relaunch Your Data Science Career with Returnships, Flexible & Hybrid Roles

Returning to work after an extended break can feel like stepping into a whole new world—especially in a dynamic field like data science. Whether you paused your career for parenting, caring responsibilities or another life chapter, the UK’s data science sector now offers a variety of return-to-work pathways. From structured returnships to flexible and hybrid roles, these programmes recognise the transferable skills and resilience you’ve gained and provide mentorship, upskilling and supportive networks to ease your transition back. In this guide, you’ll discover how to: Understand the current demand for data science talent in the UK Leverage your organisational, communication and analytical skills in data science roles Overcome common re-entry challenges with practical solutions Refresh your technical knowledge through targeted learning Access returnship and re-entry programmes tailored to data science Find roles that fit around family commitments—whether flexible, hybrid or full-time Balance your career relaunch with caring responsibilities Master applications, interviews and networking specific to data science Learn from inspiring returner success stories Get answers to common questions in our FAQ section Whether you aim to return as a data analyst, machine learning engineer, data visualisation specialist or data science manager, this article will map out the steps and resources you need to reignite your data science career.