Senior AI/ML Engineer

Kuku; Mumbai; On-site; INR 3,500,000 - 7,500,000; Full time

Job summary

Kuku is hiring a Senior AI/ML Engineer to build its AI-powered content platform, focusing on LLMs, instruction tuning, and multimodal AI for microdrama content. You will own end‑to‑end ML systems across training, evaluation, and production deployment, collaborating with content, product, and engineering teams.

The role emphasizes architecture leadership, scalable pipelines, and advanced AI techniques to transform ideas into production‑ready screenplays and video generation instructions.

Qualifications

• Bachelor's or Master's in CS/ML with 4–6 years of relevant experience.
• Experience owning and delivering complex ML/AI systems.
• Hands-on experience training or fine-tuning LLMs using PyTorch, HF Transformers, PEFT/LoRA.
• Productionising ML/GenAI systems with end-to-end data pipelines and monitoring.
• Strong knowledge of LLMs, transformers, embeddings, RAG, instruction tuning, evaluation, and agentic AI.
• Experience building LLM orchestration frameworks with LangGraph/LangChain.
• Multimodal AI experience (video understanding/generation) is desirable.
• Strong Python and software engineering fundamentals; scalable services.

Responsibilities

• Design and build LLM instruction‑tuning datasets and fine‑tune LLMs for screenplay generation.
• Build ML/LLM systems to understand transcripts and extract characters, scenes, arcs and hooks.
• Develop LLM‑powered systems that convert ideas into episode arcs and production‑ready scripts.
• Leverage multimodal AI to automate the content creation lifecycle and video generation.
• Design the intelligence layer converting screenplays into prompts for video models.
• Create agentic workflows using LangGraph to plan stories, generate scripts, rewrite and validate.
• Maintain character, location, timeline consistency across episodes.
• Design evaluation frameworks for screenplay quality and AI‑video generatability.
• Provide technical ownership in ML model formulation, experimentation, deployment.
• Define architecture and roadmap for the AI content platform; evaluate models and RAG.
• Maintain scalable training, inference, data and evaluation pipelines (MLOps).

Skills

Python

Prompt engineering

ML evaluations

Generative AI

Deep learning

Embeddings

Transformers

LangGraph

LangChain

PyTorch

Hugging Face Transformers

PEFT/LoRA

Vector databases

Education

Bachelor's or Master's in CS/ML

Tools

PyTorch

Hugging Face Transformers

PEFT/LoRA

Vector databases

Cloud platforms

MLOps

Job description

About The Job

As a Senior AI/ML Engineer, you will be instrumental in building Kuku's next-generation AI-powered content creation platform, with a focus on LLMs, instruction tuning, multimodal AI, and AI-generated microdramas. You will work on building systems that understand thousands of hours of existing microdrama content and transform creative ideas into engaging screenplays and production-ready video generation instructions.

About The Job

As a Senior AI/ML Engineer, you will be instrumental in building Kuku's next-generation AI-powered content creation platform, with a focus on LLMs, instruction tuning, multimodal AI, and AI-generated microdramas. You will work on building systems that understand thousands of hours of existing microdrama content and transform creative ideas into engaging screenplays and production-ready video generation instructions.

This role will involve working across LLM training, content understanding, agentic workflows, screenplay generation, evaluation, and AI video generation, while owning key ML systems end-to-end. You will work closely with content, product, and engineering teams to build AI systems that directly impact how stories are created at Kuku.

Responsibilities

• LLM & Instruction Tuning: Design and build large-scale instruction‑tuning datasets from Kuku's microdrama corpus and fine‑tune LLMs for screenplay generation, dialogue, story continuation, rewriting, and content transformation.
• Microdrama Intelligence: Build ML/LLM systems to understand transcripts and extract characters, relationships, scenes, story arcs, dramatic beats, hooks, conflicts, reveals, twists, and cliffhangers.
• AI Screenwriting: Develop LLM‑powered systems that transform story ideas into episode arcs, screenplays, scene breakdowns, dialogue, and structured production‑ready scripts.
• Multimodal AI & Video Generation: Build systems leveraging LLMs, VLMs, audio models, image generation, and video generation models to automate the content creation lifecycle.
• AI Video Pipeline: Design the intelligence layer that converts screenplays into structured, production‑ready prompts and instructions for video generation models such as Seedance.
• Agentic Systems & GenAI: Design and implement advanced agentic workflows using frameworks such as LangGraph to orchestrate story planning, screenplay generation, critique, rewriting, continuity validation, and video prompt generation.
• Story & Character Consistency: Build systems to maintain consistency of characters, relationships, locations, timelines, and story states across multi‑episode microdrama series.
• Evaluation & Optimization: Design evaluation frameworks for measuring screenplay quality, narrative coherence, character consistency, hook strength, cliffhanger quality, and AI‑video generatability.
• Technical Ownership: Provide technical leadership in ML model formulation, experimentation, architecture, and deployment. Take end‑to‑end ownership of critical AI systems and guide other ML engineers.
• Architecture & Strategy: Define the technical architecture and roadmap for Kuku's AI content generation platform, evaluating foundation models, fine‑tuning approaches, RAG, preference optimization, and agentic architectures.
• MLOps & Infrastructure: Design and maintain scalable, reliable, and cost‑efficient training, inference, data, and evaluation pipelines for LLM and multimodal AI systems.

Preferred Qualifications

• Education & Experience: Bachelor's or Master's in Computer Science, Machine Learning, Statistics, or a related engineering field, with 4-6 years of relevant experience, including experience owning and delivering complex ML/AI systems.
• LLM & Model Training: Hands‑on experience training or fine‑tuning large language models using frameworks such as PyTorch, Hugging Face Transformers, PEFT/LoRA, or equivalent technologies.
• Production Experience: Proven track record of productionising ML/GenAI systems, including designing and managing end‑to‑end ML systems, data pipelines, model serving, and monitoring.
• Generative AI Expertise: Strong understanding of LLMs, transformers, embeddings, RAG, instruction tuning, evaluation, and agentic AI systems.
• Agentic Systems: Experience building LLM orchestration frameworks using tools such as LangGraph, LangChain, or equivalent technologies.
• Multimodal AI: Experience working with VLMs, speech/audio models, image generation, video understanding, or video generation models is highly desirable.
• ML Evaluation: Experience designing evaluation frameworks, human preference datasets, automated evaluation, or model‑based evaluation for ML/GenAI systems.
• Strong ML Fundamentals: Strong understanding of machine learning, deep learning, NLP, transformers, embeddings, and model optimisation.
• Engineering: Strong Python programming and software engineering fundamentals with experience building scalable ML services and pipelines.
• Data & Infrastructure: Experience with distributed data processing, vector databases, cloud platforms, GPUs, or MLOps infrastructure.
• Research Awareness: Stay up‑to‑date with the latest advancements in LLMs, multimodal AI, generative AI, AI agents, and applied machine learning.

Skills: python,peft,prompt engineering,ml evaluations,generative ai,deep learning,embedding,fine tuning,multimodal ai,vector database,transformers,pytorch,langchain,lora,ai agents,llm,langgraph,machine learning,natural language processing