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About the role
Develop and fine-tune proprietary foundation models, and build multi-agent systems with autonomous reasoning, tool-calling workflows, and advanced RAG. Create curated and synthetic datasets and ensure their integrity for model pre-training, alignment, and benchmarking.
What they look for
Requirements
Requires a PhD or master's degree in computer science or a quantitative field, along with a strong record of delivering AI solutions at leading technology firms, research labs, or consulting practices. Candidates should have at least three years of specialized LLM experience, including agent design, foundation model architecture, and production-grade RAG, plus expertise with the listed frameworks and infrastructure.
Full description
Job Title- Senior Data Scientist
Location- Washington DC
Onsite- 5 days
Primarily we are looking for Sr Data Scientist who have good experience with Agents and related frameworks & use cases fit for FinTech.
What You Will Do:
- Develop Foundation Models: Contribute to the end-to-end development of proprietary foundation models and domain-specific fine-tuning (PEFT, RLHF) to solve high-stakes business challenges.
- Architect Agentic Systems: Engineer sophisticated multi-agent orchestrations, autonomous reasoning loops, and tool-calling workflows that integrate advanced RAG for complex, multi-step problem solving.
- Engineer High-Fidelity Data: Drive the synthesis of curated and synthetic datasets, ensuring data integrity for large-scale model pre-training, alignment, and benchmarking.
What You Will Bring:
- Distinguished Academia: An advanced degree (PhD or Masters) in Computer Science or a quantitative field from a world-class institution.
- Elite Industry Pedigree: A proven track record of delivering high-impact AI solutions at top-tier tech firms, AI research labs, or leading management consulting practices.
- Deep Generative AI Mastery: 3+ years of specialized experience in LLM development, including the design of autonomous agents, architectural design of foundation models, and production-grade RAG pipelines.
Technical Proficiencies:
- Frameworks: PyTorch, TensorFlow, JAX.
- Agent & LLM Orchestration: LangGraph, Semantic Kernel, CrewAI, AutoGen, LangChain, LlamaIndex.
- Fine-Tuning & Ops: DeepSpeed, LoRA/QLoRA, vLLM, Triton Inference Server.
- Data & Vector Infra: Pinecone, Milvus, Weaviate, Spark, SQL.
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