AI Trainer

MCI Careers•,

3d•Onsite

About The Position

MCI is a rapidly growing tech-enabled business services company with a significant call center presence and international operations. We offer Customer Experience (CX), Business Process Outsourcing (BPO), and Anything-as-a-Service (XaaS) cloud technology solutions across various industries. Our contact centers utilize both on-site and remote agents, employing advanced technologies to improve customer interactions, scalability, and cost-efficiency. MCI is dedicated to providing an environment where professionals can develop their careers, access ongoing learning and development, and contribute to a leading global organization. We are looking for a meticulous and analytical AI Trainer to enhance the performance, accuracy, and effectiveness of AI systems and Large Language Models (LLMs). This role involves evaluating AI outputs, creating training datasets, refining model behavior, and supporting the continuous improvement of AI-powered products and services. The ideal candidate will collaborate closely with AI engineers, prompt engineers, data annotators, and product teams to ensure AI systems deliver consistent, high-quality, accurate, and business-aligned results. To be considered, a full application on our company careers page, including screening questions and a pre-employment test, is required.

Requirements

Bachelor's Degree in Linguistics, Communications, Psychology, Computer Science, Information Systems, Data Science, Business, or a related field.
Minimum 2 years of experience in AI training, content evaluation, data annotation, quality assurance, research, or a related field.
Strong written and verbal communication skills.
Excellent attention to detail and analytical thinking abilities.
Ability to evaluate large volumes of content consistently and accurately.
Experience following detailed processes, guidelines, and quality standards.
Strong problem-solving and critical-thinking skills.
Comfortable working with large datasets and structured information.
Ability to provide constructive feedback and recommendations.
Strong organizational and time-management abilities.
Proficiency in Microsoft Office or Google Workspace.
Ability to collaborate effectively with technical and non-technical stakeholders.
Must be authorized to work in the country where the job is based.
Must be willing to submit up to a LEVEL II background and/or security investigation with a fingerprint.
Must be willing to submit to drug screening.

Nice To Haves

Experience working with Large Language Models (LLMs).
Experience in AI training, chatbot evaluation, or prompt testing.
Knowledge of Generative AI technologies.
Experience with annotation or AI evaluation platforms.
Familiarity with NLP concepts.
Experience working within technology, SaaS, or BPO environments.
Understanding of AI governance and responsible AI principles.
Exposure to machine learning workflows.

Responsibilities

Support the development and enhancement of AI systems through structured training and evaluation activities.
Train AI systems using defined methodologies and processes.
Evaluate AI-generated responses for quality, relevance, and accuracy.
Identify trends, weaknesses, and areas for model improvement.
Contribute to the refinement of model behaviors and outputs.
Help create and maintain high-quality datasets that support AI training initiatives.
Develop and review training datasets and examples.
Collaborate with data annotation teams to ensure quality standards.
Validate labeled data and training materials.
Support dataset management and maintenance activities.
Assist in improving AI performance through prompt analysis and testing.
Evaluate prompt effectiveness across multiple use cases.
Identify opportunities to improve AI response quality.
Support prompt testing and experimentation initiatives.
Collaborate with prompt engineering teams on optimization efforts.
Ensure AI systems meet organizational quality expectations.
Conduct structured evaluations of AI outputs.
Monitor performance against established benchmarks.
Document findings and recommendations.
Support quality improvement initiatives.
Contribute to the ongoing development of AI training practices.
Maintain documentation, guidelines, and training standards.
Assist with creating evaluation frameworks and procedures.
Stay informed about AI and Generative AI developments.
Recommend improvements to training processes and methodologies.