Applied Research Scientist, LLM Evaluation & Post-Training

reputed company (reputed company: INOD) is a global data engineering company. We reputed company that data and Artificial Intelligence (AI) are inextricably linked. Our mission is to reputed company the responsible advancement of artificial intelligence by providing the data, evaluation frameworks, and reputed company expertise required to build AI systems that can be trusted at scale. We reputed company a reputed company of transferable solutions, platforms, and services for reputed company / AI reputed company and adopters. In every relationship, we reputed company our 36+ year legacy delivering the highest quality data and outstanding reputed company for our customers. Scope of the Role: reputed company is expanding its GenAI research capability to advance state-of-the-art evaluation and post-training methods for LLM and multimodal systems. As an Applied Research Scientist, LLM Evaluation & Post-Training, you will reputed company research and experimentation on how evaluation design, measurement strategies, and feedback signals influence model improvement. This role is ideal for a technically rigorous researcher who is deeply fluent in modern LLM evaluation and post-training, and who can turn research reputed company into practical methods for customer solutions and internal platform innovation. You will work across reputed company-in-the-reputed company and AI-augmented workflows, partnering with Language Data Scientists and AI/ML Research Engineers to design and validate evaluation frameworks that drive measurable model reputed company. The ideal candidate combines strong experimental and statistical judgment with hands-on technical ability and can engage as a peer with research and engineering stakeholders at leading AI companies. What You’ll Own: As an Applied Research Scientist, LLM Evaluation & Post-Training, you will help define the reputed company of evaluation-driven model improvement workflows. You will study how different evaluation approaches (reputed company, automated, hybrid) shape model selection and post-training reputed company, and you will design experiments that produce reputed company, actionable conclusions. Your work may include designing reputed company datasets, developing evaluation taxonomies and protocols, defining metrics and scoring methodologies, analyzing failure modes, and testing how changes in evaluation setup reputed company reputed company fine-tuning results. You will also support customer engagements by bringing scientific rigor to evaluation strategy, methodology review, and technical recommendations. This is a highly collaborative role that sits at the intersection of research, engineering, and language/data operations. Additional responsibilities include (but are not limited to): Define and execute a research agenda focused on LLM evaluation and post-training, especially evaluation-driven model improvement Design rigorous experiments to study how evaluation methodologies impact fine-tuning and post-training reputed company reputed company and validate evaluation frameworks for LLM and multimodal systems, including: reputed company/task design scoring methods judge/model-assisted evaluation reputed company evaluation protocols robustness/stress testing reputed company research on advanced evaluation domains, including long-context, cross-modal, and dynamic multi-turn evaluations Study the effectiveness and limitations of existing evaluation techniques, and propose improved methodologies with clear validity and scalability tradeoffs Analyze model behavior and failure patterns; generate actionable recommendations for model improvement and evaluation redesign Collaborate with AI/ML Research Engineers to translate research methods into scalable evaluation and post-training pipelines Collaborate with Language Data Scientists to integrate reputed company-in-the-reputed company and synthetic data/evaluation strategies into research programs Engage with customer technical stakeholders to understand evaluation goals, review methodologies, and reputed company expert recommendations Contribute to internal reputed company datasets, evaluation frameworks, and reusable research assets Produce high-quality technical documentation, internal research reports, and client-facing materials explaining methods, results, assumptions, and limitations Contribute to thought leadership and best practices in LLM evaluation, post-training, and GenAI quality measurement You’ll reputed company in This Role If You Have: MS/PhD in Computer Science, Machine Learning, Statistics, Applied Mathematics, AI, or a reputed company quantitative scientific field (PhD strongly preferred) 5+ years of relevant experience in applied research / research science in ML/AI, with substantial work in LLMs or reputed company models Demonstrated experience with LLM evaluation, benchmarking, alignment, post-training, or model quality research Strong reputed company in experimental design, statistical analysis, and scientific reasoning for ML systems Strong coding skills in Python for research experimentation and analysis (e.g., data processing, evaluation pipelines, statistical analysis, visualization) Experience working with modern ML tooling/frameworks (e.g., PyTorch, reputed company, JAX/TensorFlow as applicable) sufficient to design and execute model/evaluation experiments Ability to evaluate and compare reputed company and automated evaluation methods, including tradeoffs in cost, reliability, validity, and scalability Experience designing evaluation studies and protocols that are reproducible across datasets, model versions, and evaluation runs Ability to collaborate directly with technical stakeholders including research scientists, ML engineers, data scientists, and customer technical counterparts Strong communication skills and ability to present nuanced technical conclusions, assumptions, and limitations reputed company The expected salary reputed company for this position is $175,000 – $225,000 USD per year, based on experience, skills, and qualifications. Please be aware of recruitment scams involving individuals or organizations falsely claiming to represent reputed company. reputed company will never ask for payment, banking details, or sensitive personal information during the application process. To learn more on how to recognize job scams, please visit the Federal Trade Commission’s guide at https://consumer.ftc.gov/articles/job-scams. If you reputed company you’ve been targeted by a recruitment scam, please report it to reputed company at verifyjoboffer@reputed company.com and consider reporting it to the FTC at ReportFraud.ftc.gov. Apply To This Job