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Disseqt AI

AI Research Scientist

Posted Yesterday
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Remote or Hybrid
Hiring Remotely in IN
Senior level
Remote or Hybrid
Hiring Remotely in IN
Senior level
Advance detection and measurement in AI systems: expand jailbreak/adversarial libraries; build bias, fairness, and hallucination evaluation methodologies; develop interpretability techniques; translate research into engineering specs and methodology docs; publish work and represent the company with customers, regulators, and at conferences.
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AI Research Scientist

Location: Bengaluru/Ireland

About Disseqt The assurance layer for enterprise AI governance Ops. Test before deployment, protect at runtime, monitor after go-live covering jailbreaks, bias, hallucination, policy violations, and regulatory compliance. Customers are Fortune 500 GSIs, financial institutions, and large enterprises navigating EU AI Act, NIST AI RMF, ISO 42001 and the unique challenges Agentic AI brings to these.

The role in one line - You advance the frontier of what's detectable and measurable in AI systems, then hand that work directly to engineers to productise. Solve hard and real world problems in building responsible and trustworthy AI with your Research that ships, not research that sits.

What you own

Research and IP development expand the jailbreak and adversarial attack library with novel methods; build bias, fairness and hallucination eval methodologies that hold up to regulators audits; develop interpretability techniques that explain why a model failed XAI (not just that it failed); maintain a live radar on AI safety literature.

Productisation bridge translate findings into engineering specs the red team and MLOps engineers can build from without hand-holding; define ground truth for eval harnesses; own the methodology documentation behind customer compliance reports.

External credibility publish papers, technical posts, benchmark releases; represent Disseqt at conferences and regulator briefings; contribute to open benchmarks where it builds community trust.

Must-haves Strong ML foundations at architecture level, not just API level. Hands on evaluation, bias, or AI safety experience. Code that runs in production, not just notebooks. Clear technical writing for two audiences (compliance officer and research peer). Genuine interest in AI governance as a space that needs to be supercharged to keep up with AI's rapid advancements and risks .

Strong signals Published work in AI safety, fairness, interpretability, or adversarial ML. LLM red teaming experience. Familiarity with EU AI Act, NIST AI RMF, ISO 42001. Prior startup experience where research had to ship.

Probably not for you if You want to work on benchmark maximisation for foundation model capabilities. You need a large team around you. You're uncomfortable with your research being used commercially and scrutinised by auditors. We will not relocate employees for this role, if candidate in Ireland you must have a visa to work in EU.

Stack Python, PyTorch, HuggingFace, open-weight and API-accessed frontier models. Fluent enough in the engineering environment to hand off cleanly not a full-stack role, but you don't stop at a notebook.

What's on offer Protected research time that doesn't get eaten by sprints. Publishing support your research output belongs to you as much as Disseqt. Direct access to live enterprise AI risk problems with global brand names in finance and beyond , not synthetic datasets. Competitive salary, meaningful equity, early-stage upside.

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