Key skills
PythonPyTorchTensorFlowRAG pipelinesVector databasesPineconeWeaviateMilvuspgvectorLangChainLlamaIndexDockerKubernetesCI/CDModel servingModel monitoringAWS SageMakerAzure MLGoogle Vertex AILarge Language Models (LLM)Fluent EnglishGoAIMachine LearningMLLLMRAGAWSAzureSageMakerVertex AI
About this role
Conquer AI is a company that deploys production-ready AI systems for major clients and is scaling fast. They are seeking a Machine Learning Engineer to design and develop ML systems, ensuring they operate effectively in live enterprise environments.
Responsibilities:
- Design and development of LLM and ML systems for client deployments
- RAG pipelines, vector search and retrieval architecture
- Fine-tuning and evaluation of models against real production data
- Deployment, monitoring and reliability once a model is live
- Agent architectures that go from proof of concept to dependable production systems
- Technical input into what's realistic to promise a client, and what isn't
Requirements:
- Fluent English required
- You've shipped models to production, not just built them in a notebook
- Strong in Python, plus PyTorch or TensorFlow
- Hands-on with RAG, vector databases (Pinecone, Weaviate, Milvus or pgvector) and orchestration frameworks like LangChain or LlamaIndex
- Comfortable with the production stack: Docker, Kubernetes, CI/CD, model serving and monitoring
- Experience with at least one major cloud ML platform (AWS SageMaker, Azure ML or Google Vertex AI)
- Comfortable working async across a globally distributed team
- AI Engineer, ML Engineer or Applied Scientist at a scale-up, tech giant or AI consultancy