Applied AI Scientist
Ask-AI
Description
Ask-AI is expanding its Research Team and is looking for full-time AI Scientists to help shape the next generation of enterprise-grade AI agents.
This is a rare opportunity to work on production-critical research at the intersection of LLMs, agentic systems, retrieval, and enterprise knowledge, directly influencing how AI systems reason, act, and scale in real-world business environments.
About Ask-AI
Ask-AI brings B2B GTM teams into the AI era by layering an agent-first architecture on a real Customer Context Layer- enriching every interaction with accurate reasoning, signal extraction, and proactive insight.
Built on more than 100 deep integrations, our platform ships five core products- Knowledge, Assist, Intelligence, Alerting, and Self-Serve- all running on shared infrastructure. Each new product we launch would have been a standalone company in the pre-AI era; for us, it’s a focused product built on a common foundation, enabling rapid, reliable releases and compounding leverage.
Our no-code Agent Builder allows teams to design and deploy agents (models, tools, triggers, actions) with governance and traceability, while the context layer powers sentiment analysis, trend detection, risk identification, and real-time alerts- modernizing customer experience end-to-end without disrupting existing workflows.
About the Role
As an AI Scientist at Ask-AI, you will own and drive end-to-end research initiatives that directly impact our core products. You will work closely with engineers, product leaders, and fellow researchers to translate cutting-edge research into scalable, production-ready systems.
You will focus on one or more of the following core areas:
- Agentic RAG Systems
- Advanced retrieval strategies, hybrid search, re-ranking, query rewriting, context compression, and multi-step LLM reasoning pipelines.
- Automatic Evaluation of AI Agents
- LLM-as-a-Judge frameworks, faithfulness and hallucination detection, trajectory evaluation, robustness testing, and scalable evaluation pipelines.
- Agents for Knowledge Creation & Maintenance
- Autonomous agents for knowledge extraction, clustering, article generation, validation, and lifecycle management in enterprise settings.
- Ontology-Grounded & Structured RAG
- Integrating domain ontologies, schemas, and structured knowledge into retrieval and reasoning loops.
- Data Analysis & Insight Agents
- Agents that analyze large-scale operational, product, and customer-support data to surface trends, risks, and actionable insights.
You will:
- Design experiments and evaluation methodologies
- Implement research prototypes and collaborate on productionization
- Influence system architecture and modeling decisions
What You’ll Gain
- Ownership over impactful, real-world AI research problems
- Direct influence on production systems used by leading B2B companies
- Collaboration with a strong, research-driven engineering culture
- Support and time for publishing in top-tier conferences
- Exposure to large-scale LLM systems, agent orchestration, and enterprise data
Requirements
Who We’re Looking For
We are looking for scientists who have:
- 3+ years of experience as a Data Scientist or ML/NLP Researcher.
- Background in Machine Learning, NLP, LLMs, Information Retrieval, or agentic systems
- Strong software engineering skills (Python required; experience with ML systems a plus)
- Ability to translate research ideas into practical, scalable systems
- Advantage - An MSc or PhD (or equivalent industry experience) in Computer Science, AI, ML, NLP, or a related field
- Advantage - Worked in a startup and is comfortable in a fast-paced environment
- Advantage - Familiarity with modern software engineering practices and tools.