6+ Audio Jobs in India

Job Title: (Generative AI Engineer Specialist in Deep Learning)

Location: Gandhinagar, Ahmedabad, Gujarat

Company: Rayvat Outsourcing

Salary: Upto 2,50,000/- per annum

Job Type: Full-Time

Experience: 0 to 1 Year

Job Overview:

We are seeking a talented and enthusiastic Generative AI Engineer to join our team. As an Intermediate-level engineer, you will be responsible for developing and deploying state-of-the-art generative AI models to solve complex problems and create innovative solutions. You will collaborate with cross-functional teams, working on a variety of projects that range from natural language processing (NLP) to image generation and multimodal AI systems. The ideal candidate has hands-on experience with machine learning models, deep learning techniques, and a passion for artificial intelligence.

Key Responsibilities:

·        Develop, fine-tune, and deploy generative AI models using frameworks such as GPT, BERT, DALL·E, Stable Diffusion, etc.

·        Research and implement cutting-edge machine learning algorithms in NLP, computer vision, and multimodal systems.

·        Collaborate with data scientists, ML engineers, and product teams to integrate AI solutions into products and platforms.

·        Create APIs and pipelines to deploy models in production environments, ensuring scalability and performance.

·        Analyze large datasets to identify key features, patterns, and use cases for model training.

·        Debug and improve existing models by evaluating performance metrics and applying optimization techniques.

·        Stay up-to-date with the latest advancements in AI, deep learning, and generative models to continually enhance the solutions.

·        Document technical workflows, including model architecture, training processes, and performance reports.

·        Ensure ethical use of AI, adhering to guidelines around AI fairness, transparency, and privacy.

Qualifications:

·        Bachelor’s/Master’s degree in Computer Science, Machine Learning, Data Science, or a related field.

·        2-4 years of hands-on experience in machine learning and AI development, particularly in generative AI.

·        Proficiency with deep learning frameworks such as TensorFlow, PyTorch, or similar.

·        Experience with NLP models (e.g., GPT, BERT) or image-generation models (e.g., GANs, diffusion models).

·        Strong knowledge of Python and libraries like NumPy, Pandas, scikit-learn, etc.

·        Experience with cloud platforms (e.g., AWS, GCP, Azure) for AI model deployment and scaling.

·        Familiarity with APIs, RESTful services, and microservice architectures.

·        Strong problem-solving skills and the ability to troubleshoot and optimize AI models.

·        Good understanding of data preprocessing, feature engineering, and handling large datasets.

·        Excellent written and verbal communication skills, with the ability to explain complex concepts clearly.

Preferred Skills:

·        Experience with multimodal AI systems (combining text, image, and/or audio data).

·        Familiarity with ML Ops and CI/CD pipelines for deploying machine learning models.

·        Experience in A/B testing and performance monitoring of AI models in production.

·        Knowledge of ethical AI principles and AI governance.

What We Offer:

·        Competitive salary and benefits package.

·        Opportunities for professional development and growth in the rapidly evolving AI field.

·        Collaborative and dynamic work environment, with access to cutting-edge AI technologies.

·        Work on impactful projects with real-world applications.

Sizzle is an exciting new startup that’s changing the world of gaming.  At Sizzle, we’re building AI to automate gaming highlights, directly from Twitch and YouTube streams. We’re looking for a superstar engineer that is well versed with AI and audio technologies around audio detection, speech-to-text, interpretation, and sentiment analysis.  

You will be responsible for:

Developing audio algorithms to detect key moments within popular online games, such as:

Streamer speaking, shouting, etc.

Gunfire, explosions, and other in-game audio events

Speech-to-text and sentiment analysis of the streamer’s narration

Leveraging baseline technologies such as TensorFlow and others -- and building models on top of them

Building neural network architectures for audio analysis as it pertains to popular games

Specifying exact requirements for training data sets, and working with analysts to create the data sets

Training final models, including techniques such as transfer learning, data augmentation, etc. to optimize models for use in a production environment

Working with back-end engineers to get all of the detection algorithms into production, to automate the highlight creation

You should have the following qualities:

Solid understanding of AI frameworks and algorithms, especially pertaining to audio analysis, speech-to-text, sentiment analysis, and natural language processing

Experience using Python, TensorFlow and other AI tools

Demonstrated understanding of various algorithms for audio analysis, such as CNNs, LSTM for natural language processing, and others

Nice to have: some familiarity with AI-based audio analysis including sentiment analysis

Familiarity with AWS environments

Excited about working in a fast-changing startup environment

Willingness to learn rapidly on the job, try different things, and deliver results

Ideally a gamer or someone interested in watching gaming content online

Skills:

Machine Learning, Audio Analysis, Sentiment Analysis, Speech-To-Text, Natural Language Processing, Neural Networks, TensorFlow, OpenCV, AWS, Python

Work Experience:  2 years to 10 years

About Sizzle

Sizzle is building AI to automate gaming highlights, directly from Twitch and YouTube videos. Presently, there are over 700 million fans around the world that watch gaming videos on Twitch and YouTube. Sizzle is creating a new highlights experience for these fans, so they can catch up on their favorite streamers and esports leagues. Sizzle is available at http://www.sizzle.gg">www.sizzle.gg. 

• Key responsibility is to design & develop a data pipeline for real-time data integration, processing, executing of the model (if required), and exposing output via MQ / API / No-SQL DB for consumption
• Provide technical expertise to design efficient data ingestion solutions to store & process unstructured data, such as Documents, audio, images, weblogs, etc
• Developing API services to provide data as a service
• Prototyping Solutions for complex data processing problems using AWS cloud-native solutions
• Implementing automated Audit & Quality assurance Checks in Data Pipeline
• Document & maintain data lineage from various sources to enable data governance
• Coordination with BIU, IT, and other stakeholders to provide best-in-class data pipeline solutions, exposing data via APIs, loading in down streams, No-SQL Databases, etc

Skills

• Programming experience using Python & SQL
• Extensive working experience in Data Engineering projects, using AWS Kinesys,  AWS S3, DynamoDB, EMR, Lambda, Athena, etc for event processing
• Experience & expertise in implementing complex data pipeline
• Strong Familiarity with AWS Toolset for Storage & Processing. Able to recommend the right tools/solutions available to address specific data processing problems
• Hands-on experience in Unstructured (Audio, Image, Documents, Weblogs, etc) Data processing.
• Good analytical skills with the ability to synthesize data to design and deliver meaningful information
• Know-how on any No-SQL DB (DynamoDB, MongoDB, CosmosDB, etc) will be an advantage.
• Ability to understand business functionality, processes, and flows
• Good combination of technical and interpersonal skills with strong written and verbal communication; detail-oriented with the ability to work independently

Functional knowledge

• Real-time Event Processing
• Data Governance & Quality assurance
• Containerized deployment
• Linux
• Unstructured Data Processing
• AWS Toolsets for Storage & Processing
• Data Security