ai/ml engineer

ABOUT THE ROLE

We're building the next generation of AI-powered personal assistant technology - a mobile-first alternative to platforms like Join us in creating an innovative platform that democratizes AI expertise and makes knowledge accessible to millions of Indians. This role requires a versatile developer who can work across the full mobile stack and contribute to backend integration.

KEY RESPONSIBILITIES

Mobile Development (70%):

• Design and develop high-performance React Native applications for iOS and Android platforms
• Implement real-time AI features including streaming chat, voice interactions, and multi-modal processing
• Build intuitive UI/UX for complex AI features (chat interfaces, voice recording, video capture)
• Integrate with device capabilities: camera, microphone, file system, notifications
• Implement offline-first architecture with smart synchronization
• Optimize app performance for low-end devices and poor network conditions
• Handle state management for complex application flows
• Implement secure authentication and authorization flows
• Build reusable component libraries and maintain design systems

Backend Integration (30%):

• Develop and maintain RESTful APIs for mobile-backend communication
• Implement WebSocket connections for real-time features
• Design efficient data synchronization strategies
• Build microservices for mobile-specific needs
• Integrate third-party APIs (OpenAI, voice services, payment gateways)
• Implement caching strategies (Redis) for performance
• Handle file upload/download with progress tracking
• Build analytics and tracking systems

Cross-functional:

• Collaborate with AI engineers to integrate ML models
• Work with designers to implement pixel-perfect UIs
• Participate in architecture decisions and technical planning
• Conduct code reviews and mentor junior developers
• Write comprehensive technical documentation
• Participate in agile ceremonies and sprint planning

MUST-HAVE TECHNICAL SKILLS

Mobile Development:

• 3-5 years of React Native development experience
  with production apps on App Store and Play Store
• Strong proficiency in
  JavaScript/TypeScript
• Deep understanding of
  React concepts
  : hooks, context, lifecycle, performance optimization
• Experience with
  React Native navigation
  (React Navigation / React Native Navigation)
• State management
  : Redux Toolkit, Zustand, or MobX
• Native module integration
  : bridging iOS (Swift/Objective-C) and Android (Java/Kotlin) code
• Experience with
  native build tools
  : Xcode, Android Studio, Gradle
• API integration
  : REST APIs, GraphQL, WebSocket
• Real-time features
  : WebRTC,
• Local storage
  : AsyncStorage, SQLite, Realm
• Testing
  : Jest, React Native Testing Library, Detox

Backend Development:

• + Express
  or
  NestJS
  for API development
• Database experience
  : PostgreSQL, MongoDB
• Authentication
  : JWT, OAuth 2.0, session management
• Strong understanding of
  RESTful API design principles
• Experience with
  cloud services
  : AWS S3, Firebase, or Google Cloud
• Version control
  : Git, GitHub/GitLab workflows

Mobile-Specific Expertise:

• Audio/Video processing
  : Recording, streaming, playback
• Device APIs
  : Camera, microphone, file system, sensors
• Push notifications
  : FCM, APNs
• Payment integration
  : Razorpay, Stripe, in-app purchases
• Analytics
  : Firebase Analytics, Mixpanel, custom event tracking
• Security
  : Secure storage, encryption, SSL pinning

HIGHLY DESIRABLE SKILLS

• AI/ML Integration experience
  : Working with LLM APIs (OpenAI, Anthropic), streaming responses
• Voice technology
  : Speech-to-text, text-to-speech, voice activity detection
• React Native libraries
  : expo-speech, @react-native-voice/voice, react-native-fs
• Performance optimization
  : Profiling, memory management, bundle size reduction
• CI/CD
  : Fastlane, App Center, GitHub Actions for mobile
• Deep linking & universal links
  implementation
• Offline-first architecture
  with conflict resolution
• Animation libraries
  : Reanimated 2, Lottie
• Cross-platform considerations
  : Platform-specific code, responsive design
• App Store optimization
  : Submission processes, compliance, ASO

TECHNICAL CHALLENGES YOU'LL SOLVE

1. Building smooth, responsive UI for AI streaming responses
2. Implementing efficient voice recording and processing in mobile environment
3. Managing complex application state across real-time AI interactions
4. Optimizing for Indian market: low bandwidth, varied devices, multiple languages
5. Creating seamless offline-to-online transitions
6. Building secure, scalable file upload systems for documents/media
7. Implementing real-time voice/video call features with AI integration

QUALIFICATIONS

Required:

• Bachelor's degree in Computer Science, Software Engineering, or related field
• 3-5 years of professional mobile development experience
• At least 2 production React Native apps
  published on both platforms
• Strong problem-solving and debugging skills
• Excellent communication skills in English
• Ability to work independently and in team settings
• Portfolio/GitHub demonstrating mobile projects

Preferred:

• Experience in AI/ML product development
• Contributions to open-source mobile projects
• Experience with fintech or edtech products
• Understanding of Indian market requirements
• Experience with Agile/Scrum methodologies

WHAT WE OFFER

Compensation:

• Competitive salary: ₹10-18 LPA
  (negotiable based on expertise in RAG/LLM)
• Additional compensation for exceptional candidates with proven track record
• Performance bonuses tied to product metrics
• Stock options (ESOP)
• Annual salary reviews

Growth & Impact:

• Work on cutting-edge AI research and applications
• Direct impact on product innovation
• Opportunity to lead AI team as we scale
• Present at conferences and publish research
• Mentorship from experienced AI leaders
• Fast-track to senior/lead roles

HIRING PROCESS

1. Resume screening
   days) - Focus on RAG/LLM experience
2. Technical phone screen
   (1 hour) - ML concepts, RAG architecture, past projects
3. Take-home project
   hours) - Build a mini RAG system with evaluation metrics
4. Technical deep-dive
   hours) - System design, live coding, ML theory
5. Final interview
   (1 hour) - Research discussion, team fit, vision alignment
6. Offer
   days)

Total timeline:
2-3 weeks