Related skills
nlp python llms langchain langgraph๐ Description
- Lead end-to-end research in NLP, vision, and multimodal AI with LLM focus.
- Architect and evaluate single-agent and multi-agent AI systems.
- Define guardrails, evaluation, and observability for AI agents.
- Translate research into production-grade, deployed solutions.
- Mentor researchers and communicate findings to stakeholders.
- Stay at the forefront of AI, shaping roadmaps and standards.
๐ฏ Requirements
- Hands-on impact in applied AI; degrees welcome but not required.
- Production-grade AI agents with multi-step reasoning and tool use.
- Agent frameworks (LangGraph/LangChain) or in-house runtimes.
- Strong expertise with LLMs (e.g., AWS Bedrock); eval and safety patterns.
- Strategic problem solving; translate questions into analytic goals.
- Proficient in Python and ML/DL libraries; HuggingFace familiarity.
- GenAI in DS workflows (LLM-as-judge, synthetic data).
- Excellent communication and mentoring; fluent in English.
๐ Benefits
- Global, growing company with opportunities to learn and grow.
- NiCE-FLEX hybrid model: 2 days in the office, 3 days remote.
- Strong engineering culture focused on practical AI impact.
- Inclusive, equal opportunity employer.
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