Sr Data Scientist GenAI
Role details
Job location
Tech stack
Job description
Sr Data Scientist (NLP / LLM / Generative AI) Location: Dallas, TX Roles & Responsibilities :
- Design, build, fine-tune, and deploy LLMs, transformer-based NLP models, and GenAI solutions for both batch and real-time/streaming contexts.
- Own all major components of ML pipelines: data ingestion, cleaning, pre-processing (structured & unstructured), embedding, search & retrieval, prompt engineering, RAG (Retrieval-Augmented Generation).
- Collaborate closely with ML Engineers, MLOps, software engineering, product, compliance, legal etc., to move models from prototype to production-ensuring reliability, scalability, monitoring, and maintainability.
- Define and implement evaluation frameworks: accuracy, bias, fairness, hallucination, consistency, latency; run UAT, stress-tests, drift detection.
- Optimize models and pipelines for performance, cost, and efficiency.
- Ensure best practices in model development: version control, repeatability, documentation, governance, and ethical AI use.
- Mentor more junior data scientists; help build team skills in NLP, GenAI practices, prompt engineering, fine-tuning.
- Identify new use cases; prototype innovations in GenAI/NLP; keep up with latest research and open source developments, decide what to adopt.
Requirements
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10+ years of experience in data science / ML, with substantial work in NLP, LLMs, or Generative AI.
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Deep hands-on experience in Python, using frameworks like PyTorch, TensorFlow, HuggingFace etc.
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Proven track record building transformer/NLP / LLM models; experience with fine-tuning, prompt engineering.
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Solid experience with information retrieval / search: keyword + semantic search, embeddings, vector databases.
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Experience working in production / deploying models (batch and streaming), working with MLOps practices.
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Strong algorithmic / statistical / mathematical fundamentals. Ability to reason about model behaviour, bias, uncertainty.
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Good communicator: able to translate complex technical detail to business / non-technical stakeholders. Nice to Have:
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Master's in Computer Science, Computational Linguistics, Statistics, Machine Learning or related field.
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Experience with multimodal models (vision + text) or emerging LLMs and agent-based systems.
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Experience with open source LLMs & toolkits; familiarity with LangChain or similar frameworks.
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Prior experience in regulated environments (finance, risk, legal, compliance) with strong governance, privacy requirements. Work remote temporarily due to COVID-19.