Machine Learning Engineer (RnD)

we're looking for a Machine Learning Engineer (R&D) who thrives in the space between experimentation and execution.

You don't need a PhD or a publication list — but you do need curiosity: the kind that makes you fine-tune a model just to see what happens, or prototype a RAG pipeline over a weekend. You've worked on real AI projects in industry, shipped code that touched users, and know that the best research is the kind that survives contact with production.

If you're mid-level with strong potential, or experienced but still hungry to explore — and you care more about what works than what's novel — this is your kind of challenge.

This is a hybrid role based in West Jakarta, where curiosity meets code.

What You'll Do:

✅ Prototype and validate AI/ML concepts for real-world use cases: NLP, RAG, agents, or GenAI workflows

✅ Build lightweight pipelines for data prep, model training, evaluation, and serving

✅ Experiment with LLM tooling: prompt engineering, fine-tuning, retrieval, caching, fallback logic

✅ Collaborate with product and engineering to turn promising ideas into testable features

✅ Document experiments, measure impact, and iterate based on results — not just intuition

✅ Stay sharp on emerging techniques, but filter them through a lens of practicality

Who You Are:

✅ 2–4 years in ML engineering, applied AI, or related roles — industry experience preferred, but strong mid-level candidates welcome

✅ Strong in Python and modern ML frameworks (PyTorch, Hugging Face, LangChain, LlamaIndex)

✅ Hands-on with LLM workflows: RAG, prompt design, evaluation, basic fine-tuning

✅ Comfortable with vector databases (Pinecone, Weaviate, pgvector) and API integration

✅ Bonus: Experience with MLOps basics (MLflow, Docker, FastAPI) or workflow tools (Dify, n8n)

✅ Fluent in English — written and spoken

✅ Nerdy enough to read a paper for fun — pragmatic enough to ask "does this actually help?"