This role sits at the intersection of multimodal AI, real-time voice, vision-language models, mobile-use agents, memory, on-device intelligence, and production-grade evaluation systems

. You will help build an AI system that can understand the user’s physical context through camera, microphones, device state and memory - then turn that context into useful action.

- Minimum 3+ years of qualified experience.

- Agentic systems
- multi-step task execution, planning and decomposition, state management

- Apply quantization (PTQ and QAT), pruning, and architecture search to hit per-product size, latency, and power budgets and efficient in working with SLM’s

- Applied vision-language models

- prompt architecture, structured output, context management, and visual understanding of interfaces, design and execute distillation strategies.

- Scale simulation and scaffolding environments for agentic RL: code execution sandboxes, computer use environments,



tool-calling harnesses, and Mobile Use Agents.

- Evaluation infrastructure

- task suites, automated scoring, regression harnesses, and success / latency / cost measurement

- Data pipelines

- capture, schema design, labelling, privacy-safe handling, and dataset curation for training

- Real-time voice

- ASR and TTS integration, streaming interaction, and end-to-end latency engineering

- Deep understanding of reinforcement learning: policy optimization, reward design, exploration, and the interplay between environment design and agent behavior.

- Model adaptation

- fine-tuning workflows, dataset construction, and running models under tight compute and memory budgets

- Partner with our mobile and hardware engineers to move capability from the cloud onto the device

📌 Applied Scientist (Multimodal AI) (India)
🏢 Invyte.ai
📍 India