Machine Learning Engineer

Permanent

West London - Hybrid

Up to £60,000

I’m supporting a global media technology organisation looking for an experienced ML/AI Engineer to help shape the intelligence capabilities within its cloud-based broadband platform.

This role will focus on applying machine learning to real-world home-networking challenges, including Wi‑Fi performance, anomaly detection, connectivity issues, and quality of experience. You’ll work with telemetry from millions of connected devices, taking models from experimentation through to scalable production deployment.

What you’ll be working on:

Developing ML models for Wi‑Fi performance prediction and classification

Detecting anomalies across home networks and CPE telemetry

Identifying the root causes of customer connectivity issues

Optimising channel selection, band steering and mesh/extender behaviour

Clustering traffic patterns and developing QoE scoring models

Building scalable pipelines for feature extraction, data ingestion, and real‑time inference

Experimenting with deep learning, time‑series forecasting, reinforcement learning, and LLM-based support agents

Developing models that remain effective when telemetry is sparse, noisy, or delayed

Integrating ML components through microservices, cloud functions, and edge‑processing environments

Working with large‑scale datasets covering millions of devices

Contributing to data models and analytics architectures for broadband and Wi‑Fi products

Collaborating with product, cloud, firmware, and hardware teams to define new ML-driven capabilities

Skills Required:

2+ years of experience in machine learning, data science, or applied AI

Strong Python skills and practical experience with TensorFlow or a comparable ML framework

Experience developing and deploying ML models within production systems

Strong analytical skills and confidence working with noisy, real‑world datasets

Understanding of Wi‑Fi standards, including 802.11a/b/g/n/ac/ax/be

Knowledge of broadband gateways, CPE, mesh networks, and Wi‑Fi extenders

Familiarity with TR-369/USP, TR-069, and broadband telemetry models

Understanding of RF and Wi‑Fi metrics such as RSSI, SNR, PHY rates, airtime, retries, congestion, DFS, and client steering

Experience with cloud or edge-based ML architectures

Exposure to LLMs applied to networking, diagnostics, or technical‑support automation

Why consider it?

You’ll join an international technology business operating at the intersection of media, cloud, broadband and connected‑home technology. The environment offers the opportunity to work on large‑scale, technically complex products while continuing to develop your skills across ML, cloud and data engineering.

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