Senior AI Fine-Tuning Engineer

Entermind AI; Kuala Lumpur; On-site; MYR 180,000 - 300,000; Full time

Job summary

Entermind AI seeks a Senior AI Fine-Tuning Engineer to lead the design, development, and deployment of custom-tuned LLMs for enterprise clients. You will translate business needs into fine-tuning strategies, architect training pipelines, and optimize inference for production-ready AI systems.

This is a senior, applied AI role focused on delivering business outcomes, including leadership of a technical team and collaboration with clients to design scalable solutions.

Qualifications

• Deep expertise in PyTorch/TensorFlow/JAX and transformer architectures.
• 6-8 years in ML/AI engineering with minimum 2 years on LLM fine-tuning, proven track record shipping production LLM systems with business impact.

Responsibilities

• Design fine-tuning strategies using SFT, instruction tuning, and RLHF (PPO/DPO).
• Build end-to-end training pipelines and distributed systems.
• Design retrieval-augmented generation systems and vector databases integration.
• Deploy models with serving infrastructure and inference optimization.
• Provide technical leadership and mentor engineers on fine-tuning best practices and MLOps.

Skills

Fine-tuning

RLHF

LoRA/QLoRA

MLOps

RAG systems

Vector DBs

Distributed training

Inference optimization

Leadership

Tools

Pinecone

Weaviate

Qdrant

Milvus

DeepSpeed

vLLM

TensorRT-LLM

Job description

We're seeking a Senior AI Fine-Tuning Engineer with 6+ years of experience to lead the design, development, and deployment of custom-tuned large language models for enterprise clients.

You will be the technical authority on model adaptation, alignment, and optimization- translating business requirements into fine-tuning strategies that deliver superior performance on domain-specific tasks. You'll architect training pipelines, implement RLHF workflows, optimize model inference, and ensure our AI systems meet enterprise standards.

This is not a research position - it's a senior engineering role focused on applied AI that ships to production and drives business outcomes.

Your Playground

Model Fine-Tuning & Alignment

• Design fine-tuning strategies using SFT, instruction tuning, and RLHF (PPO/DPO)
• Implement parameter-efficient methods (LoRA, QLoRA, Adapters) for cost-effective adaptation
• Apply constitutional AI and safety alignment techniques

Training Infrastructure & MLOps

• Build end-to-end training pipelines with distributed systems (DeepSpeed, FSDP)
• Implement experiment tracking, model versioning, and reproducibility

RAG & Hybrid Systems

• Design retrieval-augmented generation systems with semantic search
• Build and optimize vector databases (Pinecone, Weaviate, Qdrant, Milvus)

Enterprise Integration

• Deploy models with serving infrastructure (vLLM, TensorRT-LLM)
• Implement quantization (GPTQ, AWQ) and inference optimization

Technical Leadership

• Mentor engineers on fine-tuning best practices and MLOps
• Lead client technical discussions and solution design sessions

What We’re Looking For

Education:

Deep expertise in PyTorch/TensorFlow/JAX and transformer architectures

Experience:

6-8 years in ML/AI engineering with minimum 2 years on LLM fine-tuning, Proven track record shipping production LLM systems with business impact

Technical Expertise

• Model Fine-Tuning: RLHF/RLAIF (PPO, DPO), LoRA, QLoRA, instruction tuning, alignment techniques
• Open-Source LLMs: Llama 3/3.1/3.2, Mistral/Mixtral, Qwen 2.5, Falcon, Phi, Gemma
• RAG Systems: Vector databases (Pinecone, Weaviate, Qdrant), orchestration (LangChain, LlamaIndex)
• MLOps: Distributed training (DeepSpeed, FSDP), model serving (vLLM, TGI), quantization (GPTQ, AWQ)
• Data & Evaluation: Custom benchmarks, data governance, synthetic data generation

Additional Skills

• Strong technical communication with stakeholders.
• Client-facing experience in solution design.
• Leadership maturity with mentoring capabilities.

Why You'll Love It Here

• Be part of a pioneering consultancy that is shaping the future of AI-native business transformation.
• Work in cross-functional teams that blend engineering, design and strategy.
• Exposure to cutting-edge applied AI and ML initiatives across industries such as financial services, retail, telecom and insurance.
• A culture that values empathy as much as precision, giving equal weight to human experience and engineering rigour.
• Opportunities for continuous learning, growth and building a career at the intersection of AI and business.