3 Annotation Platforms Jobs

Key Responsibilities Translation Evaluation & Linguistics (70%) Evaluate and annotate LLM-generated translations for Japanese, covering nuanced, real-world usage across finance, communication, and culture. Compare AI outputs with high-quality human translations, identifying errors in phrasing, idioms, tone, and contextual accuracy. Apply annotation and scoring frameworks (e.g., BLEU, ROUGE, COMET) to ensure quality benchmarks. Provide detailed linguistic feedback to improve AI model training. AI/LLM Collaboration (30%) Work with engineers, data scientists, and project managers to share reports and linguistic insights. Contribute to building datasets and test cases through language corpora and research work. Maintain structured evaluations, documentation, and logs to support ongoing improvements. Required Qualifications Education: Bachelors or Masters in Linguistics, Translation, Language Technology, Communication, or related fields. Language Proficiency: Native or near-native fluency in (3+ Years)Japanese and strong command of English. Experience: Proven track record in translation, localization, or linguistic evaluation. Analytical Rigor: Hands-on experience in language quality evaluation, annotation, or error analysis. Technical Curiosity: Familiarity with LLMs, AI tools, or prompt engineering is an advantage. Soft Skills: Highly organized, detail-oriented, and able to communicate effectively across technical and non-technical teams. Desired Skills Experience with annotation platforms or evaluation technology. Background in corpus development, curriculum design, or language research projects. Experience in process optimization, reporting, or content operations. Location: Remote/Bangalore/Mumbai

At RNT Health Insights, we are focused on developing Breakthrough Medical Devices aimed at enhancing the accuracy of early-stage upper gastrointestinal cancer detection. Our FDA-Breakthrough designated medical devices play a vital role in real-time detection of early-stage gastric and esophageal cancers during endoscopic procedures, providing gastroenterologists with instantaneous insights and ultimately improving patient outcomes. By joining our diverse team of engineers, clinicians, and regulatory experts, you will have the opportunity to be part of a passionate group committed to pushing the boundaries of medical technology and delivering life-saving insights in real-time. We are currently seeking dedicated Full-Time Medical Data Annotators and Interns to meticulously review and annotate endoscopic video data. As part of your role, you will be responsible for accurately labeling medical images and videos to support the development of our AI-assisted cancer detection technologies. Collaboration with our clinical, engineering, and AI teams will be essential to ensure the highest quality data annotation, directly contributing to the accuracy and effectiveness of our medical solutions. Your responsibilities will include reviewing and annotating endoscopic videos and images, accurately identifying and marking abnormalities such as lesions, polyps, ulcers, and suspicious cancerous areas. Adherence to precise annotation protocols and guidelines is crucial to maintain consistency and accuracy in labeled data. Furthermore, close collaboration with clinical experts will be necessary to validate annotations and address any discrepancies. You will also be involved in quality assurance checks to uphold the standards of annotated datasets, along with meticulous documentation of annotation processes to ensure compliance with medical-device regulatory standards. Your feedback on improving annotation processes, protocols, and tools will be highly valued and instrumental in enhancing our operations. To be successful in this role, we are looking for individuals with previous experience in medical data annotation or related activities, exceptional attention to detail, strong observational skills, and a willingness to engage in repetitive tasks. A basic understanding of human anatomy and pathology, particularly in gastrointestinal diseases, is essential. Proficiency in working with computer systems, medical imaging software, and annotation platforms, along with strong communication and collaboration skills, is also required. Preferred qualifications include a Bachelor's degree or pursuing a degree in Medicine, Biology, Biomedical Sciences, Biotechnology, Nursing, or a related healthcare field. Familiarity with gastrointestinal endoscopy procedures, knowledge of medical terminology specific to gastroenterology, experience with annotation software tools such as Labelbox, CVAT, or similar, and an understanding of regulatory considerations in medical data handling (e.g., FDA, ISO 13485) are advantageous. Joining our team offers a range of benefits, including competitive compensation exceeding industry standards, the opportunity to contribute to groundbreaking medical technology that saves lives, collaboration with leading clinicians and AI researchers in a dynamic startup environment, hands-on experience with cutting-edge AI and medical-device technology, flexible work hours, and a supportive, mission-driven culture.,

You will be joining Hitech, a prominent provider of Engineering, BIM, and Business Process Solutions with a global presence and a dedicated team. Specifically, you will be part of the Data Annotation & AI Enablement division, supporting AI model training and human feedback loops for various AI applications. Currently, we are seeking a proficient Project Lead Annotation to oversee and ensure the success of our data labeling initiatives. In this role, you will take charge of managing large, diverse teams, including both internal members and external vendors, to generate high-quality annotated datasets for AI and machine learning ventures. Your responsibilities will encompass supervising project execution from start to finish, establishing annotation workflows, setting up QA pipelines, and maintaining consistent data accuracy and throughput. To excel in this position, you will need a combination of leadership skills, a structured approach to processes, and hands-on familiarity with annotation platforms and data labeling tools. The ideal candidate should possess strong communication abilities, structured thinking, and a keen enthusiasm for facilitating AI development through meticulous human-in-the-loop data management. Your key duties will include leading and organizing annotation teams, delegating tasks and milestones, monitoring progress, motivating team members, crafting and upholding annotation guidelines, implementing QA strategies to boost data quality, optimizing workflows for enhanced efficiency, collaborating with various teams, suggesting process enhancements, evaluating team performance, and efficiently managing distributed workflows through collaboration tools. For this role, we are looking for individuals with a bachelor's or master's degree in computer science, Information Technology, Data Engineering, or a related field, along with 3-6 years of experience in leading data or annotation projects. Proficiency in annotation tools like Label box, CVAT, or other custom platforms, sound knowledge of data formats such as JSON, XML, YOLO, CSV, and COCO, familiarity with QA workflows and annotation guidelines, and an understanding of AI and machine learning concepts are essential. Additionally, exceptional communication skills, problem-solving abilities, organizational prowess, and multitasking capabilities will be advantageous in this role.,