Role Overview:
We are hiring for one of our clients, seeking an AI trainer to work on a contract basis. The role involves training and refining AI models to improve accuracy and performance for enterprise applications. Candidates will collaborate with cross-functional teams to implement data-driven solutions and validate model outputs.
Key Responsibilities:
• Develop and optimize training datasets to enhance AI model performance across multiple domains.
• Evaluate AI model outputs for quality, consistency, and alignment with business objectives.
• Collaborate with data scientists and engineers to refine training methodologies and improve model interpretability.
• Document training processes, model improvements, and performance metrics for internal stakeholders.
• Conduct iterative testing to identify biases, errors, and edge cases in AI-generated responses.
Required Skills & Qualifications:
• Proficiency in natural language processing (NLP) frameworks such as Hugging Face or spaCy.
• Experience with data annotation and labeling tools for AI model training.
• Strong analytical skills to assess model performance and identify improvement areas.
• Familiarity with Python and common data processing libraries (e.g., Pandas, NumPy).
• Understanding of machine learning concepts and evaluation metrics such as precision, recall, and F1 score.
• Ability to interpret technical documentation and translate requirements into actionable training tasks.
• Experience working with large-scale datasets and distributed computing environments is a plus.
More About the Opportunity:
This role offers a unique opportunity to work with a global leader in the Information Services industry, contributing to the development of AI systems that power next-generation enterprise solutions. The position provides exposure to cutting-edge tools and methodologies in AI training and evaluation.
Equal Opportunity Employer:
We hire based on skills and expertise. All qualified candidates are welcome regardless of background, experience, or prior employment history. Applications are reviewed solely on demonstrated technical ability and qualifications.
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