Applied Audio AI Engineer II

Our client utilizes advanced models to protect against both current and emerging fabrication techniques. As a leading solution for detecting and deterring fraudulent text, audio, and visual content, they partner with government agencies and enterprise clients to enhance security and prevent fraud.

Responsibilities

• Develop and fine-tune deep learning models using PyTorch, tailored to new datasets and client needs.

• Ensure the performance and quality of deployed models through rigorous monitoring.

• Automate machine learning workflows and manage CI/CD for models used by clients.

• Optimize and compress models to improve inference speed.

• Implement security measures such as model obfuscation and vulnerability assessments.

• Collaborate with AI and Engineering teams to address infrastructure needs and improve model performance.

Skillset

• Master’s or PhD in Computer Science, with a focus on machine learning or deep learning.

• Over 2 years of Python programming experience, demonstrating strong coding skills.

• At least 2 years of industry experience in training and fine-tuning models using PyTorch.

• Preferred: Experience with fine-tuning large foundational models like wav2vec or HuBERT for specific classification tasks.

• Knowledge of automated testing and CI/CD processes in machine learning.

• Strong background in machine learning and data science.

• Effective communication and interpersonal skills, comfortable in client-facing roles.

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