Senior AI Applied Engineer (Applied ML + LLMs) | Build the AI engine for Voosh
- Tech Lead Track Voosh helps multi-location US restaurant brands win on 3rd party delivery marketplaces such as DoorDash and Uber Eats. We are now building an AI-first intelligence layer on top of our data and workflows. This role is for someone who wants real ownership early . Your work will directly move revenue, margin, and customer retention. Think $1M impact, not experiments for a slide deck. What you will build
• Response and uplift models on historical sales, order, and spend data
• Budget optimization models allocating spend across location, channel, and time window
• Measurement frameworks (test-control, difference-in-differences, causal inference) to estimate true marketing impact
• Customer segmentation models guiding where and how much to spend
• AI copilots: chatbots, NL2SQL pipelines, and analytics agents
• Production AI features that improve automation, accuracy, and decision quality First 90 days
• A baseline response model and a simple budget allocator running across multiple brands
• A repeatable impact measurement template the team uses weekly
• At least one shipped AI workflow that meaningfully cuts analyst time Who this fits
• 5+ years in Applied ML, Data Science, or ML Engineering
• Has technically led a small engineering team (2-5 engineers),



formally or as a tech lead
• Deep in Python, SQL, statistics, and messy real-world data
• Real depth in at least two of: causal inference, optimization, segmentation, forecasting, experimentation
• Has shipped LLM systems to production, not prototypes: prompting, tool calling, RAG or NL2SQL, and evals
• Has put monitoring around their own models and can say what it caught
• Bias for shipping. Builds, tests, deploys, iterates, and owns what breaks Tech stack (indicative)
• Python, SQL, sklearn/statsmodels, forecasting and causal libraries,
• feature pipelines, experiment tracking, model registry, CI/CD for
• pipelines, drift monitoring, embeddings, tool/function calling,
• structured outputs, LangChain or LlamaIndex, AWS/GCP/Azure, containers What we assess Depth of applied ML and LLM knowledge, problem solving on unfamiliar problems, accountability for production failures, ability to lead and develop engineers, and transparent communication with non-technical stakeholders. Why join You own the AI roadmap and build the brains of the business. Your models influence weekly spend decisions. You work directly with the founder. Impact is measured in dollars and retention, not slide decks. Interested? Apply here
- https://forms.gle/SzNSRnzsQsqgQ4GT9

📌 Senior AI Applied Engineer (Bengaluru)
🏢 Voosh
📍 Bengaluru