Data Scientist or AI/ML Engineer

Qualifications

Advanced Python proficiency, especially in scalable, clean code architecture and microservices (e.g., FastAPI, Flask, asyncio)Solid understanding of API integration patterns and inter-servic communication (e.g. REST, Kafka)Experience with authentication and authorization mechanisms (e.g. OAuth2, JWT, Azure AD)At least two ML/AI solutions delivered to production, ideally involving document understanding, NLP or search/retrieval systemsPractical knowledge and hands-on experience with: RAG architectures, LLMs (e.g., OpenAI, Antropic), Vector databases (e.g., FAISS, Azure AI Search), Embeddings (e.g., OpenAI)Strong grasp of NLP techniques: named entity recognition (NER), document classification, chunking, summarization, question answering.Ability to evaluate trade-offs and select appropriate ML/AI techniques for a given problem.Experience with PoC development and iterating quickly based on results.Familiarity with LangChain, LlamaIndex, or similar agentic frameworks.Strong debugging, profiling, and optimization skills for AI applications.Senior/Employment Details

Seniority level: Mid-Senior levelEmployment type: ContractJob function: Design, Engineering, and OtherIndustries: Financial Services, Banking, and Investment ..... full job details .....