Flam is building the next generation of interactive media through its content format. We are an AI-native technology company transforming how brands and consumers interact through immersive, interactive content. Our technology enables rich, app-less experiences that can be launched instantly on smartphones, creating a fundamentally different way for brands to engage consumers. We are backed by leading investors and already work with some of the world's largest brands. We are now building Flicks, our interactive media format for the US market.

About the role :

Every model we ship at Flam is bounded by the data that trained it, and every eval number we report is only as trustworthy as the eval set behind it. This role owns both. You will build and run the data layer underneath our LLM Falcon, our TTS system Finesse). That means text, audio, and video, cleaned, deduplicated,filtered,labelled, synthetically generated where real data doesn't exist, and versioned so that six months from now we can say exactly what went into a checkpoint. This is an engineering role.



You will write Python every day. It is not an annotation or labelling-management position, though you will design annotation guidelines and quality-check what comes back.

What you'll do
Build ingestion and cleaning pipelines at scale — deduplication (exact, near-dup, semantic), quality filtering with classifier-based scoring, PII stripping,language identification, format normalization.
Generate synthetic data where real data is scarce or expensive: LLM generated instruction and preference data, code-mixed Indic text, rendered scenes for image models, augmented audio for speech models.
Curate multilingual and code-mixed Indic corpora. A large part of our differentiation is Indic-language quality, and a large part of that comes down to data hygiene most pipelines get wrong.
Build and maintain evaluation sets. Design them so they measure what we think they measure, keep them uncontaminated, and version them pr

📌 Data Engineer (Bengaluru)
🏢 Flam
📍 Bengaluru