AI Research Engineer

Company: VideoSDK

Website: Visit Website

LinkedIn: Visit LinkedIn

Business Type: Startup

Company Type: Product

Business Model: B2B

Funding Stage: Seed

Industry: Information Technology

Job Description Role: AI Research Engineer – Small Language Models & On-Device AI Location: Hybrid (India)

Experience Range : 1 - 2 Years

Company Location : Surat, Gujarat

Education Background : BE/BTech in CS/IT

About VideoSDK 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.