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Zebra Technologies

AI Software Engineer

London
Posted about 15 hours ago
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Overview:

At Zebra, we are a community of innovators who come together to create new ways of working. United by curiosity and a culture of caring, we develop smart solutions that anticipate our customer’s and partner’s needs and solve their challenges.

Being part of Zebra Nation means you are seen, heard, valued, and respected. Drawing from our unique perspectives, we collaborate to deliver on our purpose. Here you are part of a team pushing boundaries today to redefine the work of tomorrow for organizations, their employees, and those they serve.

You’ll have opportunities to learn and lead in a forward-thinking environment, defining your path to a fulfilling career while channeling your skills toward causes you care about—locally and globally.

Come make an impact every day at Zebra.

What We're Looking For:

We are seeking a skilled and motivated Computer Vision Engineer to join our team. In this role, you will bridge the gap between high-level machine learning research and high-performance production environments. You will be responsible for building robust SDKs, automating deployment pipelines, and ensuring our models run efficiently across a diverse hardware landscape, from edge SoCs to powerful cloud GPUs.

Responsibilities:

  • SDK Development (C++): Design, develop, and maintain high-performance software development kits (SDKs) to expose computer vision capabilities to end-users and internal products.
  • Model Deployment and Integration: Port, convert, and deploy machine learning models across various hardware targets, including Qualcomm SoCs, Intel CPUs, and NVIDIA GPUs.
  • Performance Optimization: Use hardware-specific toolkits to optimize model throughput without sacrificing accuracy.
  • Evaluation & Benchmarking: Conduct rigorous testing and evaluation of models on target hardware to ensure performance metrics meet expectations.
  • Automation: Build and maintain automation scripts and CI/CD pipelines using Python to streamline the model testing and deployment life cycle.

Reasons to use Rodeo

I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?

Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.

Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.

Start with a chat, not a search bar

Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.

P

Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.

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It searches the market for you

Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.

Why you're a good match

You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.

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Strong

Experience fit

Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.

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Strong

Only hits

No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.

Education:

Bachelor's or master's degree in Computer Science, Electrotonic Engineering, or related technical field.

Qualifications:

  • Deep understanding of C++14/17/20, including STL, memory management, and multi-threading.
  • Strong ability to write clean, maintainable Python for automation, and data processing.
  • Hands-on experience with at least one of the following frameworks: SNPE/QNN (Qualcomm), OpenVino (Intel), TensorRT (Nvidia), TensorFlow Lite
  • Familiarity with Docker for creating consistent development and deployment environments.

Bonus:

  • Understanding Deep Learning fundamentals (CNNs, Transformers, Object Detection).
  • Experience with model conversion and quantization (i.e. PTQ, QAT).

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Incentive Compensation:

In addition to base pay, Zebra offers this role the opportunity to earn a performance-based annual cash incentive, at a target equal to 12% of base pay, in accordance with the terms of the applicable incentive plan.

Job Posting Statement:

To protect candidates from falling victim to online fraudulent activity involving fake job postings and employment offers, please be aware our recruiters will always connect with you via @zebra.com email accounts. Applications are only accepted through our applicant tracking system and only accept personal identifying information through that system. Our Talent Acquisition team will not ask for you to provide personal identifying information via e-mail or outside of the system. If you are a victim of identity theft contact your local police department.

AI Technology Statement:

Zebra Technologies leverages AI technology to evaluate job applications using objective, job-relevant criteria. This approach enhances efficiency and promotes fairness in the hiring process. However, every decision regarding interviews and hiring is made by our dedicated team, because we believe people make the best decisions about people. For more on how we use technology in hiring and how we process applicant data, see our Zebra Privacy Policy.

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“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”

Jessica, London

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Skills

C++
Python
Computer Vision
Machine Learning
SDK Development
Model Deployment
Performance Optimization
CI/CD Pipelines
Docker
TensorRT
OpenVino
SNPE/QNN
TensorFlow Lite
Multi-threading
Memory Management
Object Detection

Location

London, England, United Kingdom

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