Generative AI Annotation Operations Engineer
Sustainable TalentFull Time
Mid-level (3 to 4 years), Senior (5 to 8 years)
Candidates must possess a PhD in a mathematics-heavy technical field such as Physics, Engineering, Mathematics, or Biology. A minimum of 3-5 years of Python experience is required, along with a strong foundation in machine learning algorithms and metrics. Experience with PyTorch and TensorFlow is necessary, as is familiarity with data security concepts like encryption, masking, and tokenization. A strong curiosity and drive to become a GenAI expert are also essential qualifications.
The Machine Learning Engineer will architect and implement GenAI systems, utilizing agentic coding IDEs and designing experiments to analyze and present results. Responsibilities include conducting literature reviews on agentic AI research, fine-tuning LLMs and embedding models, and applying traditional ML algorithms to large datasets. The role also involves processing legal, compliance, and user documentation datasets, and contributing to roadmap planning and product evolution for enterprise-scale security solutions.
Data protection solutions for enterprises
Protegrity specializes in data protection for large enterprises, helping them manage data privacy, governance, and compliance. The company offers solutions such as data encryption and tokenization, which protect sensitive information by replacing it with non-sensitive equivalents. This allows organizations to use their data securely while meeting regulatory requirements. Protegrity generates revenue through service fees and subscriptions for its data protection services and consulting, where experts guide clients on enhancing their data security strategies. With the growing demand for data security due to increasing regulations and the high costs of data breaches, Protegrity is positioned to provide scalable solutions tailored to the needs of large enterprises.