Machine Learning Engineer (£70k+ + Equity) at SafetyMode at Jack & Jill/External ATS

London, England, United Kingdom -

Full Time

Start Date

Immediate

Expiry Date

12 Jun, 26

Salary

0.0

Posted On

14 Mar, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Computer Vision, Object Detection, Transformer Architectures, TFLite, YOLO, Model Training, Production Deployment, Quantization, Inference Optimization, NLP, Text Classification, ONNX Runtime, Core ML

Industry

Staffing and Recruiting

Description

This is a job that Jill, our AI Recruiter, is recruiting for on behalf of one of our customers. She will pick the best candidates from Jack's network. The next step is to speak to Jack. Machine Learning Engineer (£70k+ + Equity) Company Description: SafetyMode - Social impact AI startup protecting children online Job Description: You will own the entire detection pipeline for the world's most advanced on-device child safety technology. From dataset strategy and model training to production deployment, you will build real-time AI that identifies harmful content across all smartphone apps. This role offers the unique challenge of balancing high-performance computer vision with strict on-device privacy. Why this role is remarkable: Rare opportunity to own the end-to-end ML capability for a product with a massive social mission and high-profile backing from Sir Tim Berners-Lee and Hugh Grant. Work on cutting-edge technical challenges involving real-time, on-device inference (YOLO, Transformers, TFLite) where your code directly protects thousands of children from harm. High-impact founding team environment incubated by CanDo, with strategic partnerships including Mumsnet and Nothing Technology to scale globally. What you will do: Design and train robust object detection and transformer-based text classification models to identify various categories of online harm. Optimize model architectures for low-latency execution on Android devices using quantization, TFLite, and novel on-device inference strategies. Establish rigorous evaluation suites and automated labeling pipelines to continuously reduce false positives in complex, high-noise mobile environments. The ideal candidate: At least 2 years of experience in applied ML with a track record of shipping production-grade computer vision or NLP systems. Proficiency in modern detection pipelines (YOLO) and transformer architectures (RoBERTa/ModernBERT), with a deep understanding of precision/recall tuning. Hands-on experience with on-device optimization tools like ONNX Runtime or Core ML and a passion for solving ambiguous, high-stakes safety problems. Who are Jack & Jill? Ok, I'll go first. I'm Jack, an AI Career Agent that gets to know you on a quick call, learning what you're great at and what you want from your career. Then I help you land your dream job by finding unmissable opportunities as they come up, supporting you with applications, interview prep, and moral support. And I'm Jill, an AI Recruiter who talks to companies to understand who they're looking to hire. Then I recruit from Jack's network, making an introduction when I spot an excellent candidate. Next steps Step 1. Visit our website. Step 2. Click 'Talk to Jack'. Step 3. Talk to Jack so he can understand your experience and ambitions. Step 4. Jack will make sure Jill (the AI agent working for the company) considers you for this role. Step 5. If Jill thinks you're a great fit and her client wants to meet you, they will make the introduction. Step 6. If not, Jack will find you excellent alternatives. All for free. We never post fake jobs This isn't a trick. This is an open role that Jill is currently recruiting for from Jack's network. Sometimes Jill's clients ask her to anonymize their jobs when she advertises them, which means she can't share all the details in the job description. We appreciate this can make them look a bit suspect, but there isn't much we can do about it. Give Jack a spin! You could land this role. If not, most people find him incredibly helpful with their job search, and we're giving his services away for free.

Responsibilities

The role involves owning the entire detection pipeline for child safety technology, encompassing dataset strategy, model training, and production deployment of real-time AI to identify harmful content across smartphone apps. Responsibilities include designing and training object detection and transformer-based text classification models, optimizing architectures for low-latency on-device execution, and establishing automated labeling pipelines.