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Location: India
Department: ActAIealware
We are reimagining the phone. AI phones need to be proactive, intuitive, intelligent and low cost. This is a mission critical for rest of the world to adopt intelligence.
There are over 5 billion people using everyday applications such as email, messaging, notes, tasks, and calendars, yet most are not AI-native. Our mission is to build proactive applications and devices that bring intelligence into daily conversations, coordination and workflows, with minimal prompting.
Evaluate suitable open-weight and commercially available models for on-device execution.
Benchmark model performance on target mobile hardware.
Integrate models into Android applications and system services.
Optimize inference latency, memory consumption and power usage.
Evaluate quantization, compression and model distillation techniques.
Work with CPU, GPU and NPU acceleration.
Evaluate local model capabilities for different workflows.
Build hybrid local/cloud model routing mechanisms.
Identify which tasks can be handled locally and which require cloud inference.
Work with AI agent engineers to integrate local models into the agent runtime.
Strong ML systems or inference engineering experience.
Experience deploying and optimizing models.
Strong Python and C++ skills.
Understanding of neural network inference.
Experience with model quantization and performance optimization.
Understanding of hardware constraints and inference benchmarks.
Experience with on-device LLMs.
Qualcomm QNN, MediaTek NeuroPilot or similar acceleration frameworks.
ONNX Runtime, LiteRT, TensorFlow Lite or ExecuTorch.
Android NDK.
Mobile or edge AI deployment.
Multimodal model optimization.
From live job posts on CoreHRx, updated 14 Nov 2026. Skill figures count posts that list their skills; salary figures only posts that show a salary.
The post does not state the pay. As an estimate, comparable posts on CoreHRx advertise ₹10L – ₹25L a year (typical for IT Jobs in India, 873 posts).
It is a full time job.
Interview preparation · 60 questions
This page helps Indian job seekers prepare for Python interviews for backend, data engineering and data analyst roles, whether you are a fresher facing your first technical round or an experienced developer aiming for a senior position. It has 60 questions in three levels, easy, medium and hard, each with a concise sample answer and, where it helps, runnable Python 3.12 code. Topics include data structures, OOP, generators, decorators, the GIL and concurrency, type hints, testing and performance. Answer each question aloud in your own words first, then compare with the sample answer and run the code to check your understanding.
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