Machine Learning Engineer

videosdk.live; Surat; On-site; INR 600,000 - 900,000; Full time

Job summary

VideoSDK is looking for a Machine Learning Engineer in Surat to design, train, and optimize ML models and pipelines for real-time applications.

You will work with Python, NumPy, Pandas, and CUDA to transform data into production-ready solutions, collaborating with cross-functional teams to ship scalable AI features. Experience required: 0–2 years.

Qualifications

• 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.

Skills

Python

NumPy

Pandas

Nvidia CUDA

Statistics

ML fundamentals

Model training

Model evaluation

Data preprocessing

EDA

Git

APIs

Deploying models

Education

BE/BTech in CS/IT, AI/ML only

Tools

Git

APIs

CUDA

Job description

Job 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

• 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.