Senior Machine Learning Engineer - Deep Learning

Job Title : Senior Machine Learning Engineer - Deep Generative Models

Location : Gurugram (Work From Office)

Job Type : Full-Time

About Us

TrueFan is a leading innovator in the field of artificial intelligence and machine learning, dedicated to pushing the boundaries of technology to solve real-world problems. We are looking for a talented and motivated Machine Learning Engineer with a passion for deep generative models to join our dynamic team.

Job Description

As a Machine Learning Engineer specializing in generative models and speech synthesis, you will design, develop, and implement advanced models such as GANs, VAEs, VQ-VAEs, and Autoencoders. Additionally, you will work on Text-to-Speech (TTS) systems and voice cloning technologies to enhance our products.

Responsibilities
 Develop and implement generative models, including GANs, VAEs, VQ-VAEs, and Autoencoders.
 Design and optimize TTS systems and voice cloning algorithms.
 Conduct experiments to validate model performance and refine algorithms.
 Collaborate with cross-functional teams to integrate models into production systems.
 Analyze and interpret large datasets to guide model development.
 Stay updated with the latest research in deep generative models and speech synthesis.
 Document models, algorithms, and processes clearly and concisely.
 Participate in code reviews and contribute to the improvement of our codebase.

Qualifications
 Bachelor's or Master's degree in Computer Science, Machine Learning, or a related field.
 2+ years of experience with deep generative models, including GANs, VAEs, VQ-VAEs, and Autoencoders.
 Proficiency in Python and deep learning frameworks such as TensorFlow or PyTorch.
 Strong understanding of machine learning principles and statistical methods.
 Good to have experience with Text-to-Speech (TTS) systems and voice cloning technologies.
 Experience with data preprocessing, augmentation, and pipeline development.
 Excellent problem-solving skills and ability to work independently and collaboratively.
 Strong communication skills for conveying complex concepts to non-technical stakeholders.

Preferred Qualifications
 Experience with cloud platforms such as AWS, Google Cloud, or Azure.
 Knowledge of reinforcement learning and its applications in generative models and speech synthesis.
 Familiarity with version control systems such as Git.
 Contributions to open-source projects or published research papers in relevant fields.

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