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.