About VideoSDK:

VideoSDK is a real-time communication platform that helps developers and businesses build scalable video, voice, and interactive experiences into their applications. With powerful APIs and SDKs, VideoSDK enables teams to create custom solutions for video conferencing, live streaming, webinars, virtual classrooms, and collaborative applications without worrying about the complexities of infrastructure.

Position: Machine Learning Engineer

Location: Surat, GJ (Onsite)

Experience: 0 - 2 Years

Website: www.videosdk.live

Education: BE/BTech in CS/IT, AI/ML only.

Requirements

Must to have:

Strong proficiency in Python, including NumPy, Pandas, Nvidia CUDA.
Strong understanding of statistics, probability, linear algebra, & machine learning fundamentals.
Hands-on experience building, training, evaluating, and optimizing machine learning models / or LLMs.
Experience with data preprocessing, feature engineering, exploratory data analysis (EDA), and model evaluation.
Ability to define evaluation metrics, conduct experiments, and interpret model performance.
Familiarity with Git, APIs, and deploying models into production environments.
Strong problem-solving skills and the ability to translate business requirements into data-driven solution.

Good to have:

Familiarity with speech processing, ASR, TTS, or conversational AI.
Familiarity with inferencing frameworks.
Experience with LLMs, embeddings, vector databases, & RAG pipelines.
Knowledge of audio analytics, real-time communication data, or voice AI applications.
Understanding of MLOps, model monitoring, and production model optimization.

Erforderliche Kompetenzen

Python programming (including NumPy & Pandas)NVIDIA CUDAStatistics and probabilityLinear algebraMachine learning fundamentalsBuilding, training, evaluating, and optimizing machine learning modelsData preprocessing, feature engineering, and exploratory data analysis (EDA)Defining evaluation metrics and experiment design / interpreting model performanceGitAPIs and deploying models to production (model deployment)Experience with LLMs, embeddings, vector databases, and RAG pipelinesSpeech processing / ASR / TTS / conversational AI and audio analytics for real-time communicationInference frameworks for model servingMLOps, model monitoring, and production model optimization

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