Associate, DataX
blackrock
Job Description
Key Responsibilities
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Contribute to the design and implementation of multi-agent workflows using frameworks such as LangGraph
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Participate hands-on across the AI application lifecycle, from POC to MVP to production, including data pipelines and backend integration
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Implement and maintain evaluation and testing frameworks to assess agent behavior, reliability, and decision quality
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Support the integration of LLMs into core business products, with attention to performance, availability, and latency
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Collaborate with cross-functional teams (product, platform, data) to deliver scalable AI solutions aligned with business needs
Technical Requirements
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Strong proficiency in Python and familiarity with production-grade software engineering practices (CI/CD, unit testing, prompt testing)
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Hands-on experience building stateful, multi-step AI systems using agentic orchestration frameworks such as LangGraph
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Solid understanding of NLP fundamentals (tokenization, embeddings, semantic search) and applied data science concepts (data preprocessing, experimentation)
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Experience working with graph data structures and libraries (e.g., NetworkX) to model complex relationships
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Working knowledge of RAG architectures and vector databases
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Basic understanding of Transformer architectures and exposure to fine-tuning or adapting language models
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Familiarity with AI/ML frameworks such as PyTorch or TensorFlow, and exposure to Kubernetes or containerized deployments is a plus
Skills and Experience
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Bachelor’s or Master’s degree in Computer Science, Data Science, Mathematics or other quantitative fields
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4+ years of work experience building and deploying engineering or AI / ML systems end to end, including 6-12 months of hands-on experience in deploying LLM-based workflows (development, integration or experimentation
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Strong written and oral communications skills, with ability to explain technical concepts clearly
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Ability to manage tasks across multiple priorities and deliver high-quality components within larger projects, under guidance from senior engineers
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Curiosity and motivation to stay current with developments in generative AI and open-source language models
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Exposure to private markets or asset management is a plus but not required
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