Research Engineer - Bengaluru - Pocket FM

    Pocket FM
    Pocket FM Bengaluru

    11 hours ago

    ₹800,000 - ₹1,600,000 (INR) per year
    Description

    Research Engineer at Pocket FM

    About Pocket FM:

    • We deliver personalised and immersive audio experiences to listeners worldwide.
    • We leverage Generative AI in producing content and streamlining operations, developing innovative solutions for cutting-edge challenges in the AI landscape.

    The Role:

    Please note that this job description is a modified version of the original text. The company's budget has been removed from the output.
    1. * Design an agentic orchestration framework that selects optimal video generation models per scene, constructs and refines prompts dynamically decomposes episode-level goals into scene-level tasks manages generation validation refinement loops *
    2. • Develop automated prompt engineering strategies model selection heuristics (or learned selection policies) self-refinement critique loops quality control mechanisms LLM- vision-based evaluators • Create orchestration logic for scene continuity character consistency environment persistence Style preservation across episode Temporal coherence Budget / compute optimisation • Build evaluation frameworks measure narrative coherence Visual consistency Style fidelity Emotional alignment Anime-specific quality metrics • Optimise minimal human intervention scalable production robust failure recovery reproducibility >The Ideal Candidate You are someone with experience building agent-based orchestration engine Automated prompt generation refinement modules Model selection routing layer Episode planner hierarchical decomposition system Feedback-driven improvement loops Evaluation scoring system Production-ready pipeline end-to-end anime episode generation Your Technical Toolkit Masters PhD Computer Science AI ML related field Strong experience Large Language Models multimodal generative models prompt engineering python production ML systems Hands-on experience building agentic systems planning agents tool-using LLM systems Orchestration pipelines Deep understanding video generation models Model evaluation benchmarking experimentation frameworks Preferred Qualification Experience video diffusion text-video systems character consistency techniques LoRA embeddings adapters Scene planning hierarchical generation reinforcement learning policy learning automated content evaluation

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