Senior
AI Fine-Tuning
Engineer
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.
Equal Opportunity for Every Person
Brilliant minds know no boundaries. At Entermind, we celebrate diverse people of all backgrounds and perspectives and are committed to building an inclusive environment for all.