2 months ago
Weybridge, United KingdomSenior
Responsibilities
- Develop ML models for Wi-Fi performance prediction, classification, anomaly detection, root-cause analysis, channel selection, band steering, mesh/extender behavior, traffic clustering, and QoE scoring.
- Build scalable feature-extraction, data-ingestion, and real-time inference pipelines using cloud-based and edge-based architectures.
- Evaluate deep learning, time-series forecasting, reinforcement learning, and LLM-based agents for networking and support use cases.
- Analyze broadband gateway telemetry, CPE metrics, Wi-Fi driver outputs, and RF/Wi-Fi performance metrics.
- Integrate ML components into production systems through microservices, cloud functions, and embedded edge processing.
- Build reliable, highly available intelligence pipelines for datasets covering millions of devices.
- Collaborate with firmware, hardware, product, and engineering teams to define telemetry, event streams, and ML-driven features.
- Communicate technical results and recommendations to technical and non-technical stakeholders.
- Participate in an after-hours and weekend on-call rotation for production incidents.
Requirements
- 3–5+ years of experience in machine learning, data science, or applied AI.
- Demonstrable expertise in Python and TensorFlow or similar ML frameworks.
- Solid understanding of Wi-Fi standards 802.11a/b/g/n/ac/ax/be, broadband gateways, mesh networking, extenders, TR-369/USP, TR-069, telemetry models, home Wi-Fi KPIs, and RF fundamentals.
- Strong analytical skills and experience working with sparse, noisy, delayed, or real-world telemetry data.
- Experience applying LLMs to networking or technical support automation.
- Ability to collaborate across cloud, controller, CPE, firmware, hardware, product, and engineering environments.
Benefits
- Flexible working arrangements.
- Competitive pay hikes and bonus packages.
- Skill enhancement and growth opportunities, including resources from AWS, SkillSoft, and other partners.
- Health and wellbeing programmes.
- Collaborative work with a global team.
- Family-friendly and inclusive employment policies, engagement activities, community events, and mental health and wellbeing initiatives.