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Data Strategist
2 weeks ago
We are seeking a highly skilled Data Analyst to join our team.
The ideal candidate will bring expertise in designing, building, and scaling intelligent systems using Large Language Models (LLMs).
A deep understanding of the mechanics, ethical considerations, and trade-offs involved in deploying AI technologies is essential.
Key Responsibilities:- Create data-driven applications with a focus on modularity, scalability, and maintainability.
- Develop and fine-tune pipelines for enterprise use cases, optimizing for accuracy and relevance.
- Analyze unstructured data — documents, transcripts, APIs — and transform it into structured knowledge systems using embeddings and vector stores.
- Evaluate and select appropriate GenAI tools, frameworks, and models, balancing performance, latency, cost, and data security.
- Monitor application behavior and refine prompts and context engineering to enhance response quality.
- Identify and communicate system edge cases and risks, including hallucination, bias, and model over-reliance.
- Stay current with cutting-edge AI research and assess its potential for production use.
- Collaborate with cross-functional teams to integrate intelligent features seamlessly.
- 3–4 years of hands-on experience in AI/ML, data engineering, or full-stack development, with a strong foundation in intelligent system design.
- Deep understanding of LLMs, including concepts like embeddings, transformers, and memory strategies.
- Proven experience implementing pipelines and working with vector databases and Knowledge Graphs.
- Familiarity with GenAI frameworks and orchestration tools.
- Proficiency in Python and experience developing backend logic and integrating with APIs.
- Awareness of ethical and security concerns in AI, including safety, fairness, and responsible deployment.
- Exposure to open-source LLMs and toolkits.
- Experience with evaluation metrics, benchmarking, or implementing human-in-the-loop feedback systems.
- Familiarity with AI observability, logging, and monitoring best practices.
- Contributions to the AI community.
