Help & Supportcareers@gravityer.com
Generative AI Engineer with 1+ years in LLM Evaluation & RAG Pipelines
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Recent graduate in Computer Applications with a certification in Data Science & AI. Possesses a foundational understanding of GenAI, LLM Evaluation, and RAG Pipelines. Proven ability to design production-grade prompts, build local RAG systems, and develop LLM-powered analytics engines through hands-on projects. Eager to apply machine learning and data operations expertise gained from internships at Amazon and HEPro AI to contribute to innovative AI solutions.
Cultural Fit Analysis
The candidate's project diversity, ranging from prompt engineering and RAG systems to ML classification and data annotation, suggests adaptability. The experience at Amazon and Innodata indicates exposure to structured work environments. However, the limited information on extracurriculars or diverse team experiences makes a deep cultural fit analysis challenging. The target role of 'Generative AI Engineer' is well-aligned with the candidate's project and skill focus.
Soft Skills & Operational Fit
The candidate's resume indicates experience in collaborative environments (e.g., human-in-the-loop processes, dual-annotator consensus systems) and attention to detail (e.g., catching evaluator errors, maintaining high accuracy). However, without psychometric or English test scores, a comprehensive assessment of soft skills, work attitude, stress handling, and team collaboration is not possible.