A complete application in a minute
Tailored resume and cover letter, ready to send.
VideoSDK is seeking a hands-on Machine Learning Engineer with strong Python skills and solid mathematical foundations. You will develop, train, evaluate, and optimize ML models or LLMs, focusing on data-driven AI solutions, model experimentation, and real-time inference capabilities.
Ideal candidates have proficiency in Python (NumPy, Pandas, CUDA), strong statistics, and experience deploying models to production environments. Familiarity with GPUs and ML Ops is a plus.
About VideoSDKVideoSDK is a developer-focused platform that provides real-time audio, video, and AI communication infrastructure. Its APIs and SDKs enable developers to build scalable communication experiences and intelligent voice AI agents, including conversational AI, speech processing, and low-latency voice interactions.
Company: VideoSDK
Website: Visit Website
Business Type: Startup
Company Type: Product
Business Model: B2B
Funding Stage: Seed
Industry: Software Development
Salary Range: ₹ 3-5 Lacs PA
VideoSDK is a developer-focused platform that provides real-time audio, video, and AI communication infrastructure. Its APIs and SDKs enable developers to build scalable communication experiences and intelligent voice AI agents, including conversational AI, speech processing, and low-latency voice interactions.
The platform enables developers to integrate AI models, speech technologies, and conversational capabilities into applications without building the entire real-time communication infrastructure from scratch.
We are looking for a Machine Learning Engineer with strong Python programming skills, solid mathematical foundations, and hands-on experience developing, training, evaluating, and optimizing machine learning models or Large Language Models (LLMs).
The ideal candidate will work on data-driven AI solutions, model experimentation, performance evaluation, and production deployment. Experience in speech processing, audio intelligence, real-time conversational AI, or GPU-accelerated inference will be an added advantage.
A hands-on ML engineer who can move beyond experimentation and contribute to building, evaluating, and optimizing AI models for real-world applications. Candidates with experience in GPU acceleration, inference performance, speech technologies, or real-time AI systems will be particularly relevant.