Padmi

Ai Research Bengaluru (India)

BangalorePosted 1 month ago
Software engineeringSeniorFull Time; Regular
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Company Overview Trianz is an applied AI solutions company that accelerates customer business transformation through AI powered "Transformation Services as a Software Model". With 25+ years of transforming enterprises, weve evolved to a product-led, platform-driven organization serving global enterprises across Financial Services, Insurance, Healthcare, Hi-Tech, Manufacturing, and other industries. With global presence across 4 continents, our platform portfolio under the unified Concierto brand delivers end-to-end transformations including solutions for Migrate, Manage, Maximize, Modernize, Insights & Agentic AI, and SecOps - delivered through strategic partnerships with leading hyperscalers. Were building the premier innovation-led organization in the digital transformation space through AI-first methodologies and data-driven excellence - RevolutionAIzing Transformations. ABOUT THIS ROLE You are the operational backbone of the AI Research vertical. You execute experiments, maintain evaluation infrastructure, manage research workloads, and build the systems that enable faster, more rigorous AI research. This is a deeply hands-on role requiring expertise in LLM fine-tuning, benchmarking, evaluation frameworks, and GPU-based research operations. You will work closely with AI researchers and engineers to ensure every experiment is reproducible, measurable, and scalable. From managing benchmark datasets and model leaderboards to optimizing fine-tuning pipelines and quantization workflows, you will help drive the research organization s ability to evaluate, improve, and operationalize open-source LLMs. WHAT YOU WILL DO LLM Evaluation & Benchmarking Run LLM evaluation experiments across multiple parameter sizes using defined benchmark suites Maintain benchmark datasets including curation, versioning, quality assurance, and expansion of evaluation tasks Evaluate newly released open-source models and maintain the internal model leaderboard Measure model perf .

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