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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