Machine Learning Engineer

About VideoSDK

VideoSDK is an advanced real-time communication platform designed for developers and businesses to seamlessly integrate scalable video, voice, and interactive features into their applications. Utilizing robust APIs and SDKs, VideoSDK facilitates the creation of tailored video conferencing, live streaming, webinar, virtual classroom, and collaborative tools, allowing users to focus on development without infrastructure concerns.

Position Overview

We are seeking a Machine Learning Engineer to join our team onsite in Surat, Gujarat. The ideal candidate will possess strong skills in Python and machine learning fundamentals with 1 to 2 years of experience. The role focuses on building, training, evaluating, and optimizing machine learning models and may involve working with large language models and related technologies.

Key Responsibilities

• Develop, train, and refine machine learning models and/or large language models (LLMs).
• Perform data preprocessing, feature engineering, exploratory data analysis, and model evaluation.
• Define experiment parameters, select evaluation metrics, and interpret model outcomes effectively.
• Deploy models into production environments and manage version control using Git and APIs.
• Translate complex business requirements into meaningful data-driven machine learning solutions.

Required Qualifications and Skills

• Bachelor's degree (BE/BTech) in Computer Science, Information Technology, or specialized fields such as AI/ML.
• Proficiency in Python programming, with experience in libraries such as NumPy, Pandas, and Nvidia CUDA.
• Strong foundation in statistics, probability, linear algebra, and core machine learning concepts.
• Hands-on expertise in model training, evaluation, and optimization techniques.
• Ability to conduct comprehensive data analysis and implement robust feature engineering.
• Prior experience with Git, APIs, and production deployment practices.
• Excellent analytical and problem-solving skills aimed at data-focused business solutions.

Preferred Additional Skills

• Knowledge of speech processing technologies including ASR (Automatic Speech Recognition), TTS (Text-To-Speech), and conversational AI systems.
• Experience with inferencing frameworks and tools.
• Familiarity with LLMs, vector databases, embeddings, and Retrieval-Augmented Generation (RAG) pipelines.
• Understanding of audio analytics and real-time communication data applications, particularly in voice AI.
• Awareness of MLOps practices, model monitoring, and optimization of deployed machine learning models.