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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