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AI/ML Engineer III

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AI/ML Engineer - III


About Us

Liquidnitro Games is India’s flagship live services and game production company, founded by industry veterans with a proven track record in producing massively successful games & live services. For game companies, studios, and publishers worldwide – we offer world-class game development expertise to power creativity, growth, and profitability in their games.



What’s in it?

As an AI Engineer, you’ll play a pivotal role in building intelligent systems that unlock the full potential of our live service games. Working at the intersection of AI, data engineering, and game analytics, you’ll develop and deploy advanced machine learning and generative AI solutions to extract actionable insights, predict player behavior, and drive personalized recommendations. You will also explore agent-based automation to scale decision-making and optimize live game operations.

This role demands a strong grasp of modern AI paradigms including LLM fine-tuning, Retrieval-Augmented Generation (RAG), Agentic Workflows, Multi-Chain Prompting (MCPs), and Agent-to-Agent (A2A) interactions..



What You’ll Do

Design and implement machine learning models to process player and gameplay data at scale

Build and fine-tune LLM-based models to interpret and analyze player behavior and game telemetry

Design and deploy RAG pipelines combining structured data and unstructured content to power contextual, insight-rich recommendations

Implement agentic workflows that use goal-oriented agents for tasks like anomaly detection, churn prediction, or economy balancing

Develop multi-agent systems that can collaborate (A2A) to support live operations, AB testing, and personalized player experiences

Craft Multi-Chain Prompts (MCPs) to drive layered, complex insights and recommendations across in-game metrics

Collaborate with data engineering to maintain robust, scalable pipelines that support real-time and batch data processing

Work with game designers and producers to translate insights into live interventions and feature optimizations

Evaluate and integrate open-source LLMs, vector databases, and toolkits to keep our AI stack modern and cost-effective

Contribute to internal toolsets that empower non-technical teams with AI-powered dashboards and automation capabilities



What We’re Looking For

5+ years of experience in AI/ML, with recent hands-on expertise in LLMs or generative AI applications

Solid experience with Python and key ML/LLM frameworks (e.g., PyTorch, HuggingFace Transformers, LangChain, LlamaIndex)

Understanding of RAG, embeddings, vector search systems (e.g., FAISS, Weaviate, Pinecone), and prompt engineering

Experience building and deploying fine-tuned models using techniques like LoRA, QLoRA, or PEFT

Familiarity with orchestrating agentic workflows using tools like AutoGen, LangGraph, or OpenAgents

Experience with MLOps for training, evaluating, versioning, and deploying models in production

Experience with cloud ML and data platforms (AWS SageMaker, GCP Vertex AI, Azure ML, etc.).

Experience building/scaling AI/ML data pipelines with cloud-native tools

Proven track record of applying ML to real-world data systems at scale (especially player segmentation, recommendations, and anomaly detection)

Strong software engineering fundamentals with experience integrating AI into user-facing products or game backends




Nice to Have

Experience with game analytics platforms, telemetry ingestion, or user behavior modeling in games

Background in live service operations or experience working with economy balancing tools

Familiarity with real-time inference and GPU optimization for AI models

Understanding of AI safety, hallucination mitigation, and response grounding

Strong at mapping game development needs to practical AI applications



See also

ML / AI jobs by country — openings, pay and top skills →

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