AI Research Engineer

Position: AI Research Engineer – Small Language Models & On-Device AI
Work Type: Full Time/Hybrid (India)
Company Location: Surat, Gujarat

At VideoSDK, we’re building the real-time intelligence layer for the next generation of applications — fast, private, multimodal, and on-device.

We're hiring an AI Research Engineer to lead infrastructure development for small language models (SLMs) and speech systems, optimized for on-device multimodal AI. Your work will directly power products like real-time voice agents, live translation, intelligent video systems, and low-latency assistants — all running beyond the cloud.

What You'll Work On

• Build scalable infrastructure to train, evaluate, and deploy small language models efficiently.
  

• Design and implement RL-based training loops (e.g., PPO, DPO, RLAIF) for tuning small models in constrained environments.
  

• Work with speech systems, including speech-to-text, text-to-speech, and voice activity detection.
  

• Optimize models for on-device inference – targeting mobile, browser, and edge hardware (CPU, GPU).
  

• Contribute to building real-time multimodal AI pipelines combining text, audio, and video.
  

• Translate cutting-edge research into clean, production-ready code.
  

• Drive experiments on quantization, distillation, and architecture search for efficient deployment.
  

  
  

What We're Looking For

• Strong understanding of training, testing, and fine-tuning small models (≤2B parameters).
  

• Experience with reinforcement learning for language models (GRPO, PPO).
  

• Proven experience working with speech models (Whisper, xTTS, Silero etc).
  

• Ability to read and implement research papers quickly and effectively.
  

• Solid Python and PyTorch skills with an eye for clean, modular code.
  

• Experience with building and managing custom datasets, training pipelines, and evaluation suites.
  

• Familiarity with multimodal AI, particularly combining audio, text, or video.
  

  
  

Bonus Points

• Experience optimizing inference for mobile or edge deployments (ONNX, CoreML, TFLite, MLX, WebAssembly).
  

• Knowledge of state space models, recurrent architectures, or other attention-free designs.
  

• Contributions to open-source AI projects.
  

• Familiarity with latency-constrained or real-time systems.

  
  

Why Join VideoSDK?

We’re pushing the boundaries of real-time, personalized, multimodal AI — and doing it on the edge. You’ll work in a fast-moving environment where research meets product, and where your work directly shapes next-gen communication, assistants, and live experiences.

This is your chance to build the infrastructure behind real-time, human-like AI systems that don’t just live in the cloud — they live everywhere.