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ML Engineer / AI Platform Lead

May 2, 2026

About BTSE: BTSE Group is a global leader in fintech and blockchain technology, anchored by three core business pillars: Exchange, Payments, and Infrastructure Development. Serving over 100 corporate clients worldwide, we provide white-label exchange and payment solutions. Our offerings encompass everything from exchange infrastructure hosting and development to custody, wallets, payments, blockchain integration, trading, and more. We are looking for talented professionals in marketing, operations, customer support, and other departments. The roles offered may be on-site, remote, or hybrid, in collaboration with our local partner. About the opportunity: You own the AI core: model serving, the retrieval-augmented generation (RAG) pipeline, prompt engineering, and the feedback-to-training pipeline. In Phase 1, you make the base model perform as well as possible through context engineering — system prompts, few-shot exemplars, and retrieval optimisation — without modifying model weights. You also design the custom model training workflow so that enterprise clients can train their own fine-tuned models in Phase 2. This is the highest-leverage individual contributor role on the founding team. Responsibilities<ul> <li>Deploy and optimise a large language model for production inference: quantisation, continuous batching, low-latency serving.</li> <li>Build the RAG pipeline: document chunking, embedding generation, vector storage, cross-encoder reranking, and context assembly optimised for a 128K-token context window.</li> <li>Build the context layer: per-tenant system prompts, dynamically retrieved few-shot exemplars, task routing (classifying incoming requests to the right prompt configuration).</li> <li>Build defensive output parsing: structured JSON output from an unmodified base model with graceful fallbacks.</li> <li>Design and implement the feedback collection pipeline: capturing user corrections and ratings, automatically generating training data candidates for future fine-tuning.</li> <li>Design the custom model training workflow: tenant-scoped LoRA training on client-specific data, model evaluation, A/B testing, and isolated deployment.</li> <li>Monitor and improve inference quality: parsing failure rates, citation accuracy, hallucination rates, latency — all tracked per tenant.</li> <li>Iterate on prompts daily with the domain expert during the pilot phase.</li> </ul> Requirements<div> <ul> <li>5+ years ML engineering; 2+ years working with large language models in production.</li> <li>Hands-on experience with LLM serving frameworks (vLLM, TGI, or equivalent).</li> <li>Deep experience building RAG pipelines: chunking strategies, embedding models, vector databases, reranking.</li> <li>Strong prompt engineering skills for production applications — you know how to make a base model produce consistent, structured, high-quality output.</li> <li>Python: PyTorch, Transformers, FastAPI.</li> <li>Familiar with LoRA/QLoRA fine-tuning workflows.</li> </ul> </div> Nice to have<div> <ul> <li>Experience building multi-tenant ML serving infrastructure.</li> <li>Experience with financial or crypto AI applications.</li> <li>Experience with cross-encoder reranking models (DeBERTa or similar).</li> <li>Understanding of data isolation requirements for ML training pipelines.</li> </ul> </div> #LI-MC1

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Common Interview Questions And Answers

1. HOW DO YOU PLAN YOUR DAY?

This is what this question poses: When do you focus and start working seriously? What are the hours you work optimally? Are you a night owl? A morning bird? Remote teams can be made up of people working on different shifts and around the world, so you won't necessarily be stuck in the 9-5 schedule if it's not for you...

2. HOW DO YOU USE THE DIFFERENT COMMUNICATION TOOLS IN DIFFERENT SITUATIONS?

When you're working on a remote team, there's no way to chat in the hallway between meetings or catch up on the latest project during an office carpool. Therefore, virtual communication will be absolutely essential to get your work done...

3. WHAT IS "WORKING REMOTE" REALLY FOR YOU?

Many people want to work remotely because of the flexibility it allows. You can work anywhere and at any time of the day...

4. WHAT DO YOU NEED IN YOUR PHYSICAL WORKSPACE TO SUCCEED IN YOUR WORK?

With this question, companies are looking to see what equipment they may need to provide you with and to verify how aware you are of what remote working could mean for you physically and logistically...

5. HOW DO YOU PROCESS INFORMATION?

Several years ago, I was working in a team to plan a big event. My supervisor made us all work as a team before the big day. One of our activities has been to find out how each of us processes information...

6. HOW DO YOU MANAGE THE CALENDAR AND THE PROGRAM? WHICH APPLICATIONS / SYSTEM DO YOU USE?

Or you may receive even more specific questions, such as: What's on your calendar? Do you plan blocks of time to do certain types of work? Do you have an open calendar that everyone can see?...

7. HOW DO YOU ORGANIZE FILES, LINKS, AND TABS ON YOUR COMPUTER?

Just like your schedule, how you track files and other information is very important. After all, everything is digital!...

8. HOW TO PRIORITIZE WORK?

The day I watched Marie Forleo's film separating the important from the urgent, my life changed. Not all remote jobs start fast, but most of them are...

9. HOW DO YOU PREPARE FOR A MEETING AND PREPARE A MEETING? WHAT DO YOU SEE HAPPENING DURING THE MEETING?

Just as communication is essential when working remotely, so is organization. Because you won't have those opportunities in the elevator or a casual conversation in the lunchroom, you should take advantage of the little time you have in a video or phone conference...

10. HOW DO YOU USE TECHNOLOGY ON A DAILY BASIS, IN YOUR WORK AND FOR YOUR PLEASURE?

This is a great question because it shows your comfort level with technology, which is very important for a remote worker because you will be working with technology over time...