
Ai/ml Expert
1 week ago
**About MostEdge**
At **MostEdge**, our purpose is clear:
**Accelerate commerce and build sustainable, trusted experiences.**
With every byte of data, we strive to **Protect Every Penny. Power Every Possibility.**
We empower retailers to make real-time, profitable decisions using **cutting-edge AI**, smart infrastructure, and operational excellence. Our platforms handle:
- **hundreds of thousands of sales transactions/hour**:
- **hundreds of vendor purchase invoices/hour**:
- **few hundred product updates/day**:
- With systems built for **99.99999% uptime**
We are building an **AI-native commerce engine**, and language models are at the heart of this transformation.
**Role Overview**
We are looking for an **AI/ML Expert** with deep experience in **training and deploying Large Language Models (LLMs)** to power **MostEdge's next-generation operations, cost intelligence, and customer analytics platform**.
You will be responsible for fine-tuning domain-specific models using internal structured and unstructured data (product catalogs, invoices, chats, documents), embedding real-time knowledge through RAG pipelines, and enabling AI-powered interfaces that drive **search, reporting, insight generation, and operational recommendations.**
**Scope & Accountability**
**What You Will Own**
- Fine-tune and deploy **LLMs** for product, vendor, and shopper-facing use cases.
- Design **hybrid retrieval-augmented generation (RAG)** pipelines with LangChain, FastAPI, and vector DBs (e.g., FAISS, Weaviate, Qdrant).
- Train models on internal datasets (sales, cost, product specs, invoices, support logs) using **supervised fine-tuning and LoRA/QLoRA** techniques.
- Orchestrate **embedding pipelines, prompt tuning, and model evaluation** across customer and field operations use cases.
- Deploy LLMs efficiently on **RunPod, AWS, or GCP**, optimizing for **multi-GPU, low-latency inference**.
- Collaborate with engineering and product teams to embed model outputs in dashboards, chat UIs, and retail systems.
**What Success Looks Like**
- 90%+ accuracy on retrieval and reasoning tasks for product/vendor cost and invoice queries.
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