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Company Overview

At Synamedia, we’re a global team of 800+ trailblazers across 17 countries, revolutionizing how the world is entertained and informed.

Synamedia helps many of the world’s leading operators and media companies create, deliver and monetise next-generation video experiences across mobile and big screen. Combining integrated platforms, cloud innovation and trusted operational expertise, Synamedia enables customers to grow audiences, increase engagement, and accelerate digital transformation.

Our solutions have been built over the last three decades and are trusted by giants like Astro, Sky, beIN Sports, Vodafone, OSN, Etisalat and many more.

Ready to grow with us and shape the future of media and entertainment solutions? Let’s do it together!

About the Job – Gravity AI/ML Engineer

The Gravity AI/ML Engineer will play a pivotal role in extending and shaping the machine learning and AI implementation within Gravity Cloud service. The successful candidate will be able to implement models that to deliver innovate actionable intelligence for Gravity users.

Key Responsibilities:

• Develop ML models for:
• Wi-Fi performance prediction and classification
• Anomaly detection in home networks and CPE telemetry
• Root-cause analysis for subscriber connectivity issues
• Optimization of channel selection, band steering, mesh/Extender behavior
• Traffic pattern clustering and QoE scoring
• Build scalable pipelines for feature extraction, data ingestion, and real-time inference using cloud-based or edge-based architectures.
• Evaluate and experiment with modern AI methods (e.g., deep learning, time-series forecasting, reinforcement learning for Wi-Fi optimization, LLM-based agents for support flows).
• Work with broadband gateway telemetry (TR-369/USP, TR-069, proprietary CPE metrics, Wi-Fi driver outputs).
• Analyze RF/Wi-Fi metrics such as RSSI, SNR, PHY rates, airtime, retries, congestion, DFS, client steering data.
• Develop models that operate effectively with sparse, noisy, or delayed CPE telemetry.
• Collaborate with firmware/hardware teams to define required CPE telemetry and event streams.

Systems Integration & Deployment

• Integrate ML components into production systems via microservices, cloud functions, or embedded edge processing.
• Work with large-scale datasets (millions of devices) to build reliable, high-availability intelligence pipelines.
• Contribute to data-modeling standards and analytics architectures for broadband and Wi-Fi products.

Cross-Functional Collaboration

• Partner with product managers to define ML-driven features for home connectivity, QoE scoring, and customer-support automation.
• Work with engineering teams to ensure models are feasible across cloud, controller, and CPE environments.
• Communicate results and recommendations to technical and non-technical stakeholders
• Participate in an on-call rotation for after-hours / weekend production incidents

Technical Expertise:

Machine Learning: 3–5+ years of experience in machine learning, data science, or applied AI

ML Frameworks: Demonstratable expertise in Python, Tensor Flow, or similar

Broadband WiFi Expertise: 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, and jome Wi-Fi KPIs and RF fundamentals

Analytical Skills: Strong analytical skills and the ability to work with noisy real-world data.

LLM: Experience with LLMs applied to networking or technical support automation.