Android Software Engineer - AI

Role Overview

As an Android Software Engineer at IITMatrix, you will lead the development of Android client applications where AI functionalities are central to user experience. Your work will directly impact how AI-driven features operate, respond, and perform on mobile devices, requiring a focus on production quality, efficiency, and user-centric design.

Key Responsibilities

• Develop and maintain robust Android applications using Kotlin.
• Integrate AI-powered functionalities such as chat, vision, voice, and recommendation features through backend APIs.
• Design user experience patterns tailored for AI interactions, including managing streaming data, retry mechanisms, and partial result displays.
• Enhance app performance by optimizing memory usage, responsiveness, and managing AI-intensive operations.
• Implement comprehensive analytics, logging, and feedback systems to facilitate AI performance evaluation and iterative improvements.
• Work closely with backend and machine learning engineers to define API contracts and synchronize system behaviors.
• Maintain application stability, security, and scalability in live production environments.

Desired Experience and Skills

• Minimum of three years developing Android applications with Kotlin.
• Practical experience incorporating AI-enabled features such as language models, vision, and speech APIs.
• Strong grasp of asynchronous programming paradigms including Coroutines and Flow.
• Knowledgeable in working with RESTful or gRPC APIs and handling structured data formats.
• Proven capabilities in debugging and profiling to optimize application performance.
• Experience in managing applications under conditions of latency, partial failures, and unpredictable behaviors.
• Familiarity with MLKit or conducting lightweight on-device machine learning inference.
• Track record of releasing apps on the Google Play Store.

Expected Outcomes

• Deliver Android applications that are stable, fluid, and dependable in real-world usage.
• Ensure that applications are optimized for responsiveness, low latency, and efficient use of memory and processing power.
• Enable early detection and resolution of production problems with thorough root-cause analysis and effective monitoring.

Technical Environment

• Programming languages: Kotlin and Java
• Data management: SQL and NoSQL databases
• Machine learning tools: TensorFlow Lite for on-device inference