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Video SDK

Machine Learning Engineer

Video SDK Surat, Gujarat, India

Software Development · 51-200 employees

17 h ago
machine-learning Junior (0-2 yrs) Full-time India
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About the role

You will be responsible for building, training, evaluating, and optimizing machine learning models and LLMs. Additionally, you will define evaluation metrics, conduct experiments, and deploy models into production environments.

What they look for

Python NumPy Pandas Nvidia CUDA Statistics Probability Linear Algebra Machine Learning LLMs Data Preprocessing Feature Engineering Exploratory Data Analysis Model Evaluation Git APIs Model Deployment

Requirements

Candidates must have a degree in CS/IT or AI/ML and strong proficiency in Python and machine learning fundamentals. Hands-on experience with data preprocessing, feature engineering, and model deployment is required.

Full description

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.

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