Live opening · Posted 2 days ago

Machine Learning Engineer

SourcingXPress · Surat, Gujarat, India (On-site)
Linkedin No
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At a glance

The key details from the original listing.

Posted 2 days ago
CompanySourcingXPress
LocationSurat, Gujarat, India (On-site)
Work modeNo
SkillsMachine Learning, Python, Pandas
SourceLinkedin
ListedPosted 2 days ago

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About the role

Description supplied by the original job listing.

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
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: 1 - 2 Years
Website: www.videosdk.live
Education: BE/BTech in CS/IT, AI/ML only.
Must To Have Skills
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 solutions
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.

Work arrangement
No

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