Articul8 AI is seeking a Senior Applied AI Researcher to solve open research problems across our domain-specific GenAI platform.

Requirements

Own and orchestrate end-to-end research programs using massively parallel agentic AI — from problem formulation through production deployment.
Drive breakthrough domain-specific model quality — lead multi-stage training pipelines, domain adaptation, RL-based optimization, and training dynamics analysis.
Span modalities, methods, and domains simultaneously — design and train multimodal systems, knowledge graph pipelines, hybrid retrieval architectures, and structured reasoning systems.
Architect agentic data and training infrastructure — build agent-orchestrated pipelines for domain-specific data curation, quality filtering, preprocessing, and large-scale training.
Mentor AI Researchers in the agentic paradigm — coach team members on how to amplify their own depth and breadth.
Compress the research-to-production cycle — take prototypes to production-ready systems rapidly by leveraging agentic CI/CD, automated integration testing, and continuous evaluation harnesses.
Build force-multiplying knowledge systems — document findings, publish at top-tier venues, and contribute to internal knowledge infrastructure that agentic tools can index and reason over.
Model the augmented researcher — continuously identify bottlenecks in your own and the team's workflows, then design or adopt efficient, scalable solutions.

Articul8 AI is seeking a Senior Applied AI Researcher to solve open research problems across our domain-specific GenAI platform.

Own and orchestrate end-to-end research programs using massively parallel agentic AI — from problem formulation through production deployment.
Drive breakthrough domain-specific model quality — lead multi-stage training pipelines, domain adaptation, RL-based optimization, and training dynamics analysis.
Span modalities, methods, and domains simultaneously — design and train multimodal systems, knowledge graph pipelines, hybrid retrieval architectures, and structured reasoning systems.
Architect agentic data and training infrastructure — build agent-orchestrated pipelines for domain-specific data curation, quality filtering, preprocessing, and large-scale training.
Mentor AI Researchers in the agentic paradigm — coach team members on how to amplify their own depth and breadth.
Compress the research-to-production cycle — take prototypes to production-ready systems rapidly by leveraging agentic CI/CD, automated integration testing, and continuous evaluation harnesses.
Build force-multiplying knowledge systems — document findings, publish at top-tier venues, and contribute to internal knowledge infrastructure that agentic tools can index and reason over.
Model the augmented researcher — continuously identify bottlenecks in your own and the team's workflows, then design or adopt efficient, scalable solutions.

Senior Applied AI Researcher (India)