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