Applied ML Engineer

California

Machine Learning

Permanent

Our client, an AI startup in the music industry, is hiring an Applied Machine Learning Engineer to join the team in California. The successful candidate will combine their expertise in Machine Learning engineering and software development to build intelligent tools for music creation and streamline complex audio workflows through automation.

Responsibilities

Develop and apply machine learning algorithms to elevate their music creation tools and address real user needs.
Leverage both ready-made and custom ML solutions to deliver impactful, efficient results.
Ensure solutions are production-ready through domain shift testing, QA processes, A/B experiments and reliable deployment strategies.
Write clean, scalable, and maintainable code with a focus on enhancing product performance and user experience.
Design and manage robust data pipelines for processing audio and other unstructured data types.
Collaborate closely with Product and Engineering teams to integrate ML models seamlessly into the platform.
Fine-tune, evaluate and deploy pre-trained models for tasks such as audio analysis, melody generation and workflow automation.
Advocate for ethical and responsible AI practices, prioritizing fairness, transparency and positive user outcomes.

Skillset

Solid experience in software development using Python.
Strong track record of implementing machine learning models, particularly using PyTorch.
Hands-on experience deploying ML models in production environments; familiarity with AWS is a bonus.
Comfortable handling unstructured data, especially audio.
Strong aptitude for applied problem-solving, with a focus on quick, effective integrations.
Familiarity with generative AI architectures such as transformers, large language models (LLMs), or diffusion models.
A background or interest in music, audio production, or music technology.
Excellent communication skills with ability to work seamlessly with both technical and non-technical team members.