Ai ML Engieer
Machine Learning Engineer
Open Slots: Multiple
📍 Remote / Hybrid | Start: Immediate
Your mission?
Engineer, optimize, and deploy cutting-edge NLP and Generative AI systems directly into production. You will bridge the gap between experimental research and scalable infrastructure, turning complex unstructured data into high-throughput RAG pipelines and enterprise-ready LLM applications that don't fail under real-world load.
⚙️ STACK
- Python / scikit-learn
- PyTorch / TensorFlow
- LangChain / LlamaIndex
- OpenAI API / Vector DBs (Pinecone, Weaviate)
- Containerization: Docker / Kubernetes
- Cloud Infrastructure: AWS / GCP
🔒 CORE PROTOCOLS
01 // Production First — Notebooks prove concepts; clean, containerized MLOps code delivers revenue.
02 // Precision at Scale — Continuous monitoring, embedding optimization, and chunking strategies must withstand dirty, high-volume production datasets.
03 // Architectural Ownership — Ship complete end-to-end models, from data ingestion to low-latency API integration.