For employers

Hire this AI Trainer

Sign in or create an account to invite AI Trainers to your job.

LoginCreate account
Invite to Job
Kumar Mohit

Kumar Mohit

Agency
INDIA flag
patna, India
samyora.co
$15.00/hrIntermediate8+ISO 27001

Key Skills

Software

Other
Surge AISurge AI
ArgillaArgilla
DoccanoDoccano

Top Subject Matter

No subject matter listed

Top Data Types

TextText
Computer Code ProgrammingComputer Code Programming
ImageImage

Top Task Types

Classification
RLHF
Fine Tuning
Red Teaming
Evaluation Rating

Company Overview

Samyora is an AI and technology solutions firm that focuses on the data services, model evaluation, and scalable software engineering. Our vision is to help the creation of reliable, safe, and high-performance AI systems through the high quality of human feedback, dataset preparation, and benchmarking services. We collaborate with companies that develop large language models, machine learning applications, and AI-powered applications by providing structured data annotation, prompt evaluation, response quality rating, and model validation process. Our team comprises qualified software engineers, security experts and trained reviewers who undergo rigorous quality assurance procedures in order to produce the appropriate and consistent results. Samyora is also building contemporary web platforms, SaaS infrastructure, and AI integrations, which helps us to learn the complete lifecycle of AI product development, creating data pipelines through production systems. Our assessment procedures focus on explicit guidelines, multi layer assessment and data handling security practices. Our mission is to assist AI enterprises in having reliable human intelligence pipelines that enhance model performance, safety and real world application. Samyora is a distributed workforce based in India, with scalable operational procedures that have allowed us to undertake the workload of projects that involve data labeling, model benchmarking, and AI evaluation tasks.

IntermediateHindi

Security

Security Overview

Samyora has very strict data security and data privacy standards both are to protect the safety of the client data at every stage of the AI training and evaluation process. Sensitive datasets are blocked by role-based access controls and authenticated access controls. All its team members operate under the conditions of confidentiality and data internal operations which do not permit unauthorized access, copying or sharing of client data. Secure project workspaces, datasets control, and monitored evaluation piping make up our work processes. We are more concerned with the concepts of secure development, data transmission, and limited access when working with proprietary datasets or the products of artificial intelligence models to reduce the risk to the minimum. Another component of workforce training introduced by Samyora that presents the annotators and evaluators with the understanding of how to utilize data responsibly, how to keep privacy, and what compliance should be expected is security awareness. The project information is handled in separate environments with different audit controls and assessment systems to assure quality and standards of security. As a technology firm that has a history of working in cybersecurity and software engineering, we prioritize the design of secure systems and effective data governance processes in facilitating AI model training, benchmarking and evaluation processes.

Security Credentials

ISO 27001

Labeling Experience

Argilla

Large Language Model Response Evaluation (RLHF)

ArgillaTextRLHFFine Tuning
Considered responses of big language models on an extensive range of prompts to enhance model alignment, response quality, and post-prompt instruction. The annotators evaluated several responses made by AI and ranked their responses in relation to the accuracy, relevance, helpfulness, and safety. The project adhered to RLHF-style evaluation processes such as ranking responses, structured scoring and guideline-based feedback generation. To ensure quality assurance, multi-level review processes, annotation guidelines and interrater consistency checks were conducted to ensure that the labels were accurate. The data comprised conversational prompts that were general knowledge, technical, and reasoning. The project helped to enhance conversational AI systems, and the behavior of the models to be more suitable to user interactions in the real-world environment.

Considered responses of big language models on an extensive range of prompts to enhance model alignment, response quality, and post-prompt instruction. The annotators evaluated several responses made by AI and ranked their responses in relation to the accuracy, relevance, helpfulness, and safety. The project adhered to RLHF-style evaluation processes such as ranking responses, structured scoring and guideline-based feedback generation. To ensure quality assurance, multi-level review processes, annotation guidelines and interrater consistency checks were conducted to ensure that the labels were accurate. The data comprised conversational prompts that were general knowledge, technical, and reasoning. The project helped to enhance conversational AI systems, and the behavior of the models to be more suitable to user interactions in the real-world environment.

Present