Deep Learning Engineer

We are an innovative AI-powered music platform that’s transforming how people create, explore, and experience music. Our product leverages cutting-edge AI technologies to provide personalized music recommendations and unique features tailored to every music enthusiast.

As we continue to grow, we’re looking for a Deep Learning Engineer who will play a crucial role in driving our growth and helping us reach millions of music lovers worldwide.

What You’ll Do:

• Design, develop, and optimize deep learning models for tasks involving generation and diffusion, with a preference for applications in audio processing.

• Implement, fine-tune, and evaluate state-of-the-art architectures, including diffusion models and other generative frameworks.

• Collaborate with the research team to adapt and innovate on existing algorithms for unique challenges.

• Develop pipelines for data preprocessing, augmentation, and efficient training of large-scale models.

• Monitor and analyze model performance using metrics, ensuring alignment with project goals.

• Stay updated with the latest advancements in generative models

• Collaborate with engineering teams to integrate models into production systems and optimize for scalability and efficiency.

Who You Are:

• Experienced: You have 3+ years of professional experience in deep learning, with hands-on work involving generative models.

• Mathematically Proficient: Strong foundation in linear algebra, probability, and optimization, enabling a deep understanding of model mechanics.

• Innovative: You thrive on creating and refining state-of-the-art models, finding new ways to tackle challenging generative tasks.

• Detail-Oriented: You rigorously test and fine-tune models to ensure high-quality outputs.

• Collaborative: You communicate effectively with multidisciplinary teams to align technical work with broader objectives.

Preferred Skills:

• Strong proficiency with frameworks like PyTorch or TensorFlow.

• Experience in designing and training diffusion models, GANs, VAEs, or transformers.

• Knowledge of audio processing techniques and familiarity with libraries like librosa or torchaudio.

• Understanding of large-scale training strategies, distributed training, and GPU/TPU optimization.

• Familiarity with prompt-based or conditioned generation tasks.

• Experience with cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes).

• Background in handling datasets for audio, image, or text generation tasks.

What We Offer:

• A chance to work on a groundbreaking AI product in the music industry.

• A supportive and dynamic startup culture where your ideas and contributions truly matter.

• Flexible work environment

• Opportunities for professional growth, development and option to become a core part of executive team