
Data Scientist
4 days ago
Overview:
Data Scientist (Generative AI & Agents)
Role overview
Principal Responsibilities:
What you’ll do
- Work with GenAI models: Fine-tune and evaluate LLMs for retrieval-augmented generation (RAG), classification, and summarization tasks.
- Contribute to agentic systems: Assist in developing multi-agent or tool-using workflows using frameworks like LangChain, LangGraph, and ADK.
- Data engineering: Prepare large datasets, ensure data quality, and build pipelines for both structured and unstructured data.
- Evaluation & safety: Help design metrics, test harnesses, and guardrails for generative AI systems.
- Collaborate cross-functionally: Work closely with senior engineers and product teams to translate business needs into experiments and prototypes
Position Requirements:
- 3-4 years of experience in data science, applied ML, or analytics.
- Strong foundations in statistics, experimental design, and optimization.
- Proficiency in Python (pandas, scikit-learn, PyTorch/TensorFlow, or equivalent).
- Hands-on experience with at least one cloud platform (AWS, GCP, or Azure).
- Familiarity with GenAI concepts: LLMs, embeddings, and vector databases.
Nice to Have:
- Exposure to agent frameworks (LangChain, LangGraph, ADK).
- Experience with MLOps and observability tools (MLflow, W&B, langsmith) and deployment workflows.
- Knowledge of information retrieval or RAG pipelines.
- Interest in model evaluation, fairness, privacy, and safety in AI.
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