AI Research Engineer

videosdk.live; Surat; Hybride; INR 1 200 000 - 2 200 000; Plein temps

Résumé du poste

VideoSDK in India is seeking an AI Research Engineer to build scalable infrastructure for small language models and speech systems, optimized for on-device multimodal AI. You will enable real-time voice agents, live translation, and low-latency assistants running on edge devices.

You will work on RL-based training loops, multimodal data pipelines, and deployment for mobile and browser platforms, collaborating with researchers and engineers to ship production-ready systems.

Qualifications

• Experience training small language models (≤2B parameters).
• Proficient in Python and PyTorch for research and prototyping.
• BE/BTech in CS/IT required or equivalent.

Responsabilités

• Build scalable infrastructure to train, evaluate, and deploy small language models efficiently.
• Design RL-based training loops (PPO, DPO, RLAIF) for constrained environments.
• Work with speech systems (speech-to-text, text-to-speech, VAD) and on-device inference.
• Collaborate to build real-time multimodal AI pipelines integrating text, audio, and video.
• Translate research into clean production-ready code and run experiments on model optimization.

Connaissances

Python

PyTorch

Small language models

RL training loops

Speech models

Multimodal AI

Research to production

Dataset management

On-device AI

Formation

BE/BTech in CS/IT

Outils

Whisper

xTTS

Silero

ONNX

WebAssembly

Description du poste

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.