Senior Data Scientist

Senior Data Scientist page is loaded## Senior Data Scientistlocations: Singaporetime type: Full timeposted on: Posted Todayjob requisition id: JR Joining Razer will place you on a global mission to revolutionize the way the world games. Razer is *

• a place to do great work**, offering you the opportunity to make an impact globally while working across a global team located across 5 continents.

Razer is also *

• a great place to work,*
• providing you the unique, gamer-centric #LifeAtRazer experience that will put you in an accelerated growth, both personally and professionally.

## *

• Job Responsibilities :*
• We are seeking a highly skilled and innovative Data Scientist to join our software team, leveraging user configuration data and software configuration schemas to fine-tune large language models (LLMs) in the 8B-32B parameter range.

You will build an AI-powered configuration assistant that combines LLM fine-tuning, prompt engineering, retrieval-augmented generation (RAG) with VectorDB & GraphDB, and model optimization (including quantization) to deliver accurate, fast, and cost-effective recommendations to users. This is a full-stack applied AI role, covering data handling, model training, deployment, monitoring, and optimization in production.

• Key Responsibilities1.

LLM Fine-tuning & Evaluation Fine-tune and adapt LLMs for domain-specific configuration assistance.

• Apply instruction tuning, LoRA, RLHF, and domain adaptation.
• Establish automated evaluation pipelines for accuracy, latency, and safety.
• 2.

Prompt Engineering Design, test, and optimize prompt strategies for varied scenarios, personas, and workflows.

• Develop reusable prompt templates and dynamic context injection logic.
• Run A/B tests to measure prompt impact on user outcomes.
• 3.

Retrieval-Augmented Generation (RAG) with VectorDB & GraphDB Implement semantic retrieval with *

• VectorDB** (e.g., FAISS, Pinecone, Weaviate).
• Build *
• GraphDB** (e.g., Neo4j, TigerGraph) pipelines to represent and query configuration relationships.
• Combine embedding search with graph reasoning for richer context in LLM outputs.
• Optimize retrieval for both latency and relevance.
• 4.

Model Quantization & Optimization Apply quantization, pruning, and distillation to right-size LLMs for deployment.

• Benchmark trade-offs between quality, speed, and cost across CPU/GPU/edge.
• Collaborate with infrastructure teams on inference optimization.
• 5.

Data Handling & Engineering Extract, clean, and structure configuration and schema data (JSON, YAML, XML).

• *
• Proficiency with SQL*
• for querying and transforming relational datasets.
• Build automated pipelines for continuous retraining and RAG index updates.
• Apply schema-aware data modeling for improved retrieval and training.
• 6.

Production Deployment & Monitoring Collaborate with software engineers to integrate AI into live products.

• Develop APIs and microservices for LLM-powered features.
• Set up monitoring dashboards, drift detection, and feedback loops.
• Implement safety guardrails to prevent hallucinations and unsafe recommendations.
• 7.

Security, Privacy & Compliance Ensure compliance with data privacy regulations (e.g., GDPR, SOC 2).

• Apply data anonymization and access control practices.
• Design output filtering to avoid sensitive or incorrect recommendations.

## Pre-Requisites :*

• RequirementsMust-Have: 3+ years in Data Science, ML, or NLP with hands-on *
• LLM fine-tuning*
• experience.
• Proven skills in *
• prompt engineering*
• and *
• RAG pipeline development**.
• Experience with *
• VectorDB*
• and *
• GraphDB*
• integration.
• Hands-on experience with *
• model quantization*
• and optimization.
• Proficiency in *
• Python** (Hugging

Face Transformers, PyTorch, LangChain).

• *
• Proficiency with SQL*
• and relational data modeling.
• Knowledge of YAML, JSON, XML, and schema-based data structures.
• Strong grasp of MLOps principles for production deployment.
• Preferred: Experience with GPU optimization tools (ONNX Runtime, TensorRT).
• Background in software configuration management systems.
• Familiarity with CI/CD, Docker, Kubernetes for ML services.
• Experience in LLM evaluation frameworks (e.g., Ragas, HELM, OpenAI Evals).

At Razer, youll be at the forefront of the most exciting industry in the world — gaming. Evolving forms of gaming require evolving forms of hardware, software and services. Thats where Razer comes in, offering innovative top-of-the-line products and services to allow gamers to fully immerse in the ultimate gaming experience.

Getting onboard Razer will place you on a global mission to bring gamers closer to the games they love. Razer is a place to do great work, offering you the opportunity to be a part of a global team across 11 countries. Whether you are a hardcore evangelist who breathe life to the latest and greatest gaming gear or a behind-the-scene hero who runs our global operations, you are assured of a career-changing quest that transcends time zones and culture with one single spell: For Gamers.

By Gamers. The journey towards phenomenal-ness wont come easy. However, we will excel because gamers rely on teamwork.

We achieve greatness because we are wicked problem-solvers and tenacious in clinching victories in all that we do. It is the team that makes Razer where it is today and will continue to bring Razer to even greater heights. Razer is proud to be certified as a

Great Place to Work in both United

States and Singapore. This is a testament to our commitment to make your quest at Razer a rewarding one

Information :

• Company : Razer USA Ltd.
• Position : Senior Data Scientist
• Location : Singapore
• Country : SG