LLM Engineer

We’re Hiring: LLM Engineer

We’re looking for an LLM Engineer to join our team on a 3-month remote contract. You’ll work closely with our engineering and product teams to build, fine-tune, evaluate, and deploy LLM-powered systems for real-world applications.

Company Description:-

Transit Terminal is a next-generation digital platform for global freight booking, built to bring precision, speed, and control to logistics operations. The platform enables businesses to book and manage end-to-end freight seamlessly, covering inland transport and ocean shipping through a unified, technology-driven interface. By integrating directly with carriers and logistics networks, Transit Terminal delivers real-time visibility, instant booking, and reliable execution across global trade routes. Its core systems use advanced data and AI-driven optimization to simplify complex logistics decisions, improve efficiency, and increase operational transparency. The company’s mission is to transform logistics from fragmented, manual workflows into a structured, intelligent, and highly efficient system that helps businesses move goods globally with clarity and confidence.

Job Details

• Position: LLM Engineer
• Work Mode: Remote
• Contract: 3 Months
• Compensation: ₹30,000/month
• Experience: 0–2 years
• Joining: Immediate / Short Notice Preferred

What You’ll Do

• Build and integrate LLM-powered applications and AI features.
• Fine-tune open-source LLMs for specific tasks and use cases.
• Prepare, clean, structure, and validate datasets for model fine-tuning.
• Implement fine-tuning approaches such as LoRA and QLoRA.
• Work with frameworks and tools such as Hugging Face Transformers, PEFT, and TRL.
• Experiment with different models, datasets, hyperparameters, and training strategies.
• Evaluate fine-tuned models against relevant benchmarks and real-world use cases.
• Develop RAG pipelines, AI agents, and multi-step LLM workflows.
• Work with embeddings, vector databases, semantic search, chunking, retrieval, and reranking.
• Design effective prompting and structured-output strategies.
• Integrate LLMs with backend APIs, databases, and external services.
• Optimize models and pipelines for accuracy, latency, reliability, and cost.
• Build production-ready AI services with appropriate logging, monitoring, and error handling.
• Collaborate with backend, frontend, and product teams to integrate AI capabilities into applications.

What We’re Looking For

• Strong programming skills in Python.
• Solid understanding of LLMs and modern generative AI systems.
• Hands-on experience working with LLM APIs such as OpenAI, Anthropic, Gemini, or similar.
• Practical experience fine-tuning LLMs, preferably using Hugging Face.
• Understanding of LoRA/QLoRA, PEFT, and model training workflows.
• Understanding of dataset preparation and data quality for fine-tuning.
• Experience with RAG pipelines and vector databases.
• Good understanding of prompt engineering and structured outputs.
• Experience building APIs using FastAPI, Flask, or similar frameworks.
• Familiarity with Git/GitHub.
• Strong problem-solving, experimentation, and debugging skills.
• Ability to work independently in a remote environment.

Good to Have

• Experience with LangChain, LangGraph, LlamaIndex, or similar frameworks.
• Experience building AI agents and agentic workflows.
• Familiarity with MCP (Model Context Protocol).
• Experience with vector databases such as Pinecone, Qdrant, Weaviate, or pgvector.
• Experience with Docker and CI/CD.
• Familiarity with AWS or other cloud platforms.
• Experience with LLM evaluation and observability.
• Experience working with open-source models such as Llama, Qwen, Mistral, Gemma, or similar.
• Understanding of quantization and inference optimization.
• Experience deploying fine-tuned models into production.
• Experience optimizing GPU usage, inference latency, and LLM costs.

Why Join Us?

• Fully remote opportunity.
• Work on real-world AI products and production applications.
• Hands-on experience with LLM fine-tuning, RAG, AI agents, and model deployment.
• Exposure to modern AI infrastructure and open-source models.
• Work closely with a hands-on engineering and product team.
• Opportunity for future collaboration based on performance and requirements.

If you're passionate about LLMs and want to build, fine-tune, and deploy practical AI systems, we'd love to hear from you.

• 👉 Apply through LinkedIn.