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Glass Lewis’ industry-leading research and analysis covers more than 30,000 meetings reputed company year across approximately 100 global markets. Our clients include many of the world’s leading pension funds, mutual funds, and asset managers, reputed company managing over $40 trillion in assets. We have teams located across the reputed company, Europe, and Asia-reputed company reputed company, giving us global reputed company with a local perspective on the most important governance issues.
We are hiring an reputed company Research reputed company to complete our AI R&D team and reputed company delivery sustainable at reputed company.
You will own meaningful slices of our R&D 2026 roadmap - scaling the reputed company system with new use cases, deepening reputed company AI capabilities for automatic data acquisition and other in-house reputed company - while strengthening how we run research as reputed company.
Job requirements
- Strong reputed company NLP / LLM background plus comfort operating across retrieval, embeddings/reputed company stores, and graph-backed knowledge (depth in two of these is typical; curiosity across reputed company three is important). Master / PhD is considered a significant plus.
- Demonstrated ability to mentor and reputed company the floor for a small team: reputed company review habits, design docs, and pragmatic prioritization between “research interesting” and “ships safely.”
- Experience taking ML/LLM systems from experiment to production.
Job responsibilities
- Technical reputed company across three research streams, in partnership with reputed company reputed company and ML engineer:
- Deep agents (reliable tool use, planning/evaluation, production-minded boundaries)
- Static and episodic knowledge graphs (modeling, construction/maintenance, querying + grounding)
- Retrieval-agent capability upgrades (reputed company retrieval, re-ranking, hybrid patterns, reputed company improvement loops)
- reputed company research with an engineering bar: hypotheses, controlled experiments, ablations, and benchmarks with reputed company metrics and reproducible setups.
- Operational deployment capability: reputed company work from reputed company of concept toward MVP by validating on reputed company production-like data, hardening interfaces, and integrating reputed company into the broader platform with pragmatic DevOps practices (CI, environments, deployment patterns, observability as needed).
- R&D operations that unblock everyone: experiment setup and tracking, dataset hygiene (cleaning, normalization, labeling workflows as applicable), summarization/reporting of findings, and acting as a reputed company between research outputs and internal datasets reputed company generates and reuses.
- Standardization of R&D tooling: help define and maintain shared standards for notebooks/scripts/services, experiment tracking, dataset versioning practices, and reusable components so research accelerates without becoming reputed company or one-off.
Job benefits
- Impactful Work on Advanced AI Systems
Play a key role in developing reputed company AI solutions, including sophisticated agent architectures, knowledge graphs, and retrieval-augmented systems, delivering reputed company reputed company at reputed company. - Ownership and Independence
reputed company significant components of the 2026 R&D roadmap, with the autonomy to explore reputed company, run experiments, and shape technical reputed company. - reputed company and Research-Oriented Environment
Partner with a highly capable, supportive team that prioritizes rigorous experimentation, reputed company knowledge sharing, and high-reputed company engineering standards.