AI Engineer - R&D

About Us

At whj.ai, we are pushing the boundaries of what's possible with artificial intelligence. We are currently expanding our Research & Development team and are looking for passionate problem-solvers to help us innovate, experiment, and build with Large Language Models (LLMs).

The Role

We are hiring for our R&D and LLM team! Whether you are a brilliant junior developer hungry to prove yourself, or a seasoned senior architect who has been building ML systems for years, we want to hear from you. We don't care about arbitrary years of experience—we care about your understanding of the technology, your curiosity, and your ability to execute.

If you love keeping up with the latest AI papers, experimenting with new models, and turning research into reality, this is the place for you.

What You’ll Be Doing:

• Research & Experimentation: Test, evaluate, and benchmark state-of-the-art LLMs (open-source and proprietary) to solve complex problems.

• Prototyping: Rapidly build and iterate on AI-driven prototypes and proof-of-concepts for whj.ai.

• Prompt Engineering & Fine-Tuning: Optimize model outputs, design robust prompt architectures, and potentially fine-tune models for specific use cases.

• System Integration: Work alongside the broader engineering team to integrate LLM capabilities into scalable applications.

• Staying Ahead: Continuously monitor the fast-paced AI landscape to bring new techniques, tools, and methodologies into our R&D pipeline.

What We’re Looking For:

• A Builder's Mindset: You are deeply curious and love tinkering with AI tools, frameworks, and APIs.

• Technical Chops: Strong programming skills, ideally in Python, with a solid grasp of software engineering fundamentals.

• LLM Knowledge: A clear understanding of how Large Language Models work, their capabilities, and their limitations (hallucinations, context limits, etc.).

• Adaptability: The ability to learn incredibly fast in a domain that changes week to week.

• Strong Communication: The ability to translate complex AI concepts into plain language for the rest of the team.

Bonus Points (Nice to Have, Not Required):

• Experience with orchestration frameworks (LangChain, LlamaIndex, etc.).

• Experience working with Vector Databases (Pinecone, Weaviate, Milvus, etc.) and RAG pipelines.

• Familiarity with ML frameworks (PyTorch, TensorFlow).