Qube Cinema

Provides DCI-compliant digital cinema solutions

AI Engineer - Digital Transformation

Applied Machine Learning +1Confirmed live in the last 24 hours

Full-timeChennai, Tamil Nadu, IndiaNo salary listedIn-person

About the Job

Requirements

Requires a B.Tech, M.Tech, or M.Sc. in Computer Science, Data Science, Electrical Engineering, or a related field.
Requires 2–5 years of hands-on experience in AI engineering, data engineering, or applied machine-learning roles.
Requires a strong portfolio or demonstrated experience building and shipping AI-powered products.
Requires proficiency with Python, including pandas, NumPy, scikit-learn, FastAPI, SQLAlchemy, and Jupyter.
Requires R skills in data wrangling, statistical modelling, ggplot2, and Shiny for dashboards.
Requires SQL proficiency, including complex queries, window functions, and common table expressions, and experience with data warehouses such as Snowflake, BigQuery, or PostgreSQL.
Requires experience with LLM APIs, including OpenAI and Anthropic Claude API, and prompt engineering, function/tool calling, and retrieval-augmented generation pipelines.
Requires REST API development and consumption, JSON, OAuth, and webhook patterns.
Requires Git and GitHub or GitLab for version control, code review, and continuous integration pipelines.
Requires Linux/Bash scripting, cron, and server-side automation.
Requires experience with PyTorch or TensorFlow for deep-learning model training.
Requires comfort working in a cross-functional team with shifting priorities.

Responsibilities

Build and deploy LLM-powered bots, agents, and natural-language query interfaces for business use cases.
Integrate Claude, OpenAI, and other large language model APIs into production workflows.
Design agentic workflows with tool use, retrieval-augmented generation, and multi-step reasoning.
Develop and maintain AI integrations with Microsoft Teams, customer relationship management systems, enterprise resource planning systems, and internal platforms.
Build and maintain data pipelines connecting enterprise resource planning, customer relationship management, Slate, and the Qube Data Lake.
Write complex SQL queries, design data models, and optimize analytical workloads.
Use Python libraries and R for data transformation, modelling, and visualization.
Support business-intelligence dashboard development with clean, well-structured data layers.
Develop, train, and evaluate machine-learning and deep-learning models.
Work on applied computer-vision tasks, including super-resolution from 2K to 4K.
Set up GPU training pipelines, manage datasets, and track experiments using MLflow or an equivalent tool.
Collaborate with research partners, including IIT Madras, to operationalize research outputs.
Build and maintain workflow-automation pipelines for business-process automation.
Develop REST API integrations, webhooks, and event-driven pipelines between systems.
Implement and manage low-code automation tools as part of broader engineering workflows.
Create reusable automation scripts and continuous-integration-friendly deployment patterns.
Work with the Lead — Digital Transformation to translate business requirements into technical solutions.
Document model performance, data schemas, API contracts, and deployment guides.
Participate in architecture reviews and technical decision-making.
Deliver active projects including a sales query bot integrated with Microsoft Teams; a 2K-to-4K AI super-resolution model with IIT Madras; P&L and revenue analytics dashboards using ERP and the Data Lake; CRM data pipeline engineering across ERP, Qube Central, and Slate; and IP rights management using blockchain architecture.

Desired Qualifications

Familiarity with Claude Code for agentic coding, custom-agent development, and MCP integrations.
Familiarity with Emergent AI and experience deploying agents on the platform.
Experience with n8n workflow orchestration, custom nodes, and API chaining.
Experience with computer vision, including image super-resolution and ESRGAN, Real-ESRGAN, or similar architectures.
Experience with MLflow, DVC, or similar tools for experiment tracking, model registry, and reproducibility.
Experience with Docker and containerization for packaging models and services for deployment.
Familiarity with blockchain/Web3 basics, including Hedera or similar platforms for intellectual-property and rights use cases.
Experience with vector databases such as Pinecone, Weaviate, or pgvector for embedding-based retrieval.

About Qube Cinema
Qube Cinema is India's leading cinema technology company, powering digital cinema distribution, content localisation, and advanced analytics across thousands of screens. Our Digital Transformation team is building the intelligence and engineering layer that drives automation, AI, and data across the business.

Role Overview
We are looking for an AI Engineer to build and deploy AI-powered solutions, data pipelines, and automation workflows at Qube Cinema. You will work on a diverse set of problems — from LLM-powered bots and NLP query interfaces to super-resolution AI models and data engineering. This is a builder role where you will ship real products that transform how Qube operates.

Key Responsibilities

LLM Applications & AI Agent Development

Build and deploy LLM-powered bots, agents, and NLP query interfaces for business use cases
Integrate Claude, OpenAI, and other LLM APIs into production workflows
Design agentic workflows with tool-use, retrieval-augmented generation (RAG), and multi-step reasoning
Develop and maintain AI integrations with Microsoft Teams, CRM, ERP, and internal platforms

Data Engineering & Analytics

Build and maintain data pipelines connecting ERP, CRM, Slate, and the Qube Data Lake
Write complex SQL queries, design data models, and optimise analytical workloads
Use Python (pandas, dbt, SQLAlchemy) and R for data transformation, modelling, and visualisation
Support BI dashboard development with clean, well-structured data layers

AI & ML Model Development

Develop, train, and evaluate machine learning and deep learning models
Work on applied computer vision tasks including super-resolution (2K to 4K upscaling)
Set up GPU training pipelines, manage datasets, and track experiments (MLflow or equivalent)
Collaborate with research partners (e.g., IIT Madras) to operationalise research outputs

Automation & Integration Engineering

Build and maintain workflow automation pipelines for business process automation
Develop REST API integrations, webhooks, and event-driven pipelines between systems
Implement and manage low-code automation tools as part of broader engineering workflows
Create reusable automation scripts and CI-friendly deployment patterns

Collaboration & Documentation

Work closely with the Lead — Digital Transformation to translate business requirements into technical solutions
Document model performance, data schemas, API contracts, and deployment guides
Participate in architecture reviews and technical decision-making

Technical Skills

Core (Required)

Python — pandas, NumPy, scikit-learn, FastAPI, SQLAlchemy, Jupyter
R — data wrangling, statistical modelling, ggplot2, Shiny (for dashboards)
SQL — complex queries, window functions, CTEs; experience with data warehouses (Snowflake, BigQuery, PostgreSQL)
LLM APIs — OpenAI, Anthropic Claude API; prompt engineering, function/tool calling, RAG pipelines
REST API development and consumption; JSON, OAuth, webhook patterns
Git, GitHub/GitLab — version control, code review, CI pipelines
Linux/Bash — scripting, cron, server-side automation
Deep learning frameworks — PyTorch or TensorFlow for model training

Added Advantage

Claude Code (Anthropic) — agentic coding, custom agent development, MCP integrations
Emergent AI — platform familiarity and agent deployment experience
n8n — workflow automation orchestration, custom nodes, API chaining
Computer vision — image super-resolution, ESRGAN, Real-ESRGAN, or similar architectures
MLflow, DVC, or similar — experiment tracking, model registry, reproducibility
Docker, containerisation — packaging models and services for deployment
Blockchain / Web3 basics — familiarity with Hedera or similar for IP/rights use cases
Vector databases — Pinecone, Weaviate, pgvector for embedding-based retrieval

What You Will Work On
Active projects include: an NLP sales query bot integrated with Microsoft Teams; a 2K-to-4K AI super-resolution model in collaboration with IIT Madras; P&L and revenue analytics dashboards on ERP and Data Lake; CRM data pipeline engineering across ERP, Qube Central, and Slate; and IP rights management using blockchain architecture. You will ship across all of these.

Qualifications

B.Tech / M.Tech / M.Sc. in Computer Science, Data Science, Electrical Engineering, or related field
2–5 years of hands-on experience in AI engineering, data engineering, or applied ML roles
Strong portfolio or demonstrated experience building and shipping AI-powered products
Comfort working in a fast-paced, cross-functional team with shifting priorities

What We Offer

Hands-on work with frontier AI tooling — LLMs, agents, computer vision, and more
Collaboration with IIT Madras on applied research projects
Direct ownership of AI products used across thousands of cinema screens
Competitive compensation, flexible working, and a builder culture

About the Company

Qube Cinema

Provides DCI-compliant digital cinema solutions

Qube Cinema provides end-to-end digital cinema technology and solutions for exhibitors, filmmakers, and post-production houses. Its products, like the Qube XP I Server and Qube Xi 4K Integrated Media Block, are hardware-software platforms that store, manage, and playback DCI-compliant content, handling encryption, scheduling, and on-screen delivery. The company differentiates itself through deep cross-domain expertise in film, video, audio, and computer tech, plus a practical, installation-focused approach that expands electronic delivery, including reference deployments in Malaysia. Its goal is to enable a global, seamless digital cinema ecosystem by offering reliable, DCI-compliant hardware and software that make electronic delivery and theatrical exhibition easier and more affordable.

Company size: 1,001-5,000
Company stage: Not listed
Total funding: Not listed
Headquarters: Chennai, India
Founded: 1986

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