Mid-level Machine Learning Engineer specializing in GenAI, LLMs, and real-time ML systems
Tejal already has a relationship with Reval, so a warm intro from us gets a much better response than cold outreach.
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Built and deployed a production long-form article summarization system using BART/T5/PEGASUS, tackling real-world constraints like token limits, latency/quality tradeoffs, and factual drift via chunking/merge logic and constrained decoding. Uses pragmatic Python-based pipeline orchestration (scheduled jobs, modular scripts, logging/retries) and iterates with stakeholder feedback to make outputs genuinely useful for content workflows.
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