AI/ML Engineer - II
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