AI Research Scientist
WINDSoftArgentina8 hours ago
Full-timeRemote FriendlyEngineering, Information Technology
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As an AI Research Associate / Applied AI Engineer, you will play a key role in designing, building, and deploying applied AI solutions that enhance Cherre’s data intelligence platform. You will work across the full lifecycle — from prototyping agentic systems to production-level deployment.
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Key Responsibilities
• Design and build AI pipelines using frameworks such as LangGraph, CrewAI, n8n, and LangChain to develop modular, testable, and composable agents.
• Build and scale RAG / Graph-RAG / fine-tuned LLM solutions for real estate data normalization, enrichment, summarization, and analytics.
• Develop agent patterns that reason over tools, retrieve context, and execute multi-step goals.
• Collaborate with engineers, product managers, and domain experts to turn POCs into robust production systems.
• Contribute to internal frameworks and standards for evaluating and debugging agents (LangFuse, OpenTelemetry, or custom tracing systems).
• Experiment with memory systems, vector search, and knowledge graph integration to drive dynamic personalization and logic-based chaining.
• Participate in agent simulation testing and MCP-based design for safe, reusable AI behaviors.
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Required Skills & Experience
• 1–3 years of hands-on experience in applied ML or LLM research/engineering.
• Proven experience building agentic systems using LangGraph, CrewAI, n8n, Flowise, or LangChain.
• Proficient in Python, with experience in GCP, SQL, and DBT.
• Strong foundation in statistics (hypothesis testing, regression, time series).
• Practical experience applying NLP and transformer-based models in production workflows.
• Deep understanding of RAG, Graph-RAG, vector stores, and dynamic tool orchestration.
• Experience using LangFuse (or similar) for tracing and observability.
• Background in real estate, financial services, or other structured yet messy data domains.
• Contributions to open-source agent/orchestration libraries are highly valued.
(Note: All items above are must-have requirements.)
⸻
Why You Should Apply
• Fully remote, distributed-first culture.
• Competitive compensation & stock options.
• Flexible working hours and work-life balance.
• Unlimited vacation & paid parental leave.
• Educational credits for continued learning.
• Inclusive, collaborative, and innovation-driven environment.
⸻
Key Responsibilities
• Design and build AI pipelines using frameworks such as LangGraph, CrewAI, n8n, and LangChain to develop modular, testable, and composable agents.
• Build and scale RAG / Graph-RAG / fine-tuned LLM solutions for real estate data normalization, enrichment, summarization, and analytics.
• Develop agent patterns that reason over tools, retrieve context, and execute multi-step goals.
• Collaborate with engineers, product managers, and domain experts to turn POCs into robust production systems.
• Contribute to internal frameworks and standards for evaluating and debugging agents (LangFuse, OpenTelemetry, or custom tracing systems).
• Experiment with memory systems, vector search, and knowledge graph integration to drive dynamic personalization and logic-based chaining.
• Participate in agent simulation testing and MCP-based design for safe, reusable AI behaviors.
⸻
Required Skills & Experience
• 1–3 years of hands-on experience in applied ML or LLM research/engineering.
• Proven experience building agentic systems using LangGraph, CrewAI, n8n, Flowise, or LangChain.
• Proficient in Python, with experience in GCP, SQL, and DBT.
• Strong foundation in statistics (hypothesis testing, regression, time series).
• Practical experience applying NLP and transformer-based models in production workflows.
• Deep understanding of RAG, Graph-RAG, vector stores, and dynamic tool orchestration.
• Experience using LangFuse (or similar) for tracing and observability.
• Background in real estate, financial services, or other structured yet messy data domains.
• Contributions to open-source agent/orchestration libraries are highly valued.
(Note: All items above are must-have requirements.)
⸻
Why You Should Apply
• Fully remote, distributed-first culture.
• Competitive compensation & stock options.
• Flexible working hours and work-life balance.
• Unlimited vacation & paid parental leave.
• Educational credits for continued learning.
• Inclusive, collaborative, and innovation-driven environment.
Key Skills
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