Founding Research ML Engineer (Agentic Systems)

Founding Research ML Engineer (Agentic Systems)

Pavo\’s mission is to achieve Enterprise Superintelligence by building a self-learning autonomous platform that helps run an organization, turning every decision into a compounding competitive advantage. Our first product on this mission is the autonomous full-stack machine learning engineer, acting as a dedicated AI team member to empower engineering and product teams to integrate sophisticated ML into their products. We enable companies to see a measurable business impact from ML in weeks, not years.

We are a well-funded, early-stage startup backed by leading investors, and we are looking for passionate builders and innovators to join us on our mission.

Our Team

Our current team is a small group of PhDs in ML and ML engineers from top applied ML and coding agent companies, with proven experience in building and scaling products that serve hundreds of millions of users. The team has collectively published over 75 papers and collaborates with researchers from select US & Canadian universities.

The Role: Research ML Engineer (Agentic Systems)

As a Research ML Engineer focused on Agentic Systems, you will be at the core of Pavo\’s mission, building the foundational technologies for enterprise superintelligence. This role transcends traditional ML engineering; you will architect the memory, reasoning, and learning capabilities of our autonomous agents, tackling unsolved problems in long-horizon planning, knowledge representation, and agentic learning by combining state-of-the-art research with world-class engineering.

If you are a world expert in search, retrieval, or reinforcement learning who is driven to define the future of agentic AI, this is your ideal role.

What You\’ll Do

• Build Foundational Agent Memory: Design and scale the foundational long-horizon memory and knowledge infrastructure that enables agents to learn, recall, and reason over vast, evolving enterprise contexts. This is not about RAG; it\’s about pioneering the future of agent memory.
• Innovate in Search & Retrieval: Develop state-of-the-art search and retriever systems with multi-stage retrieval, novel indexing techniques, and new forms of knowledge representation.
• Define Agentic Learning: Apply deep expertise in reinforcement learning and reasoning to guide and advance agentic behavior, tackling complex, multi-step tasks.
• Create Synthetic Worlds: Contribute to synthetic world models and complex simulation environments where agents can train, experiment, and learn at a massive scale.
• Architect for Scale: Design, build, and deploy robust, enterprise-grade systems for a future of trillion-agent interactions, supporting cloud and on-prem deployments.

What We Are Looking For

• 5+ years of industry or academic experience as a Machine Learning Engineer, Applied Scientist, or Research Scientist.
• World-class expertise in one of the following areas:
• Search & Retrieval: Deep experience designing and scaling state-of-the-art systems (e.g., multi-stage retrieval, dense retrieval, novel indexing).
• Reinforcement Learning & Reasoning: Deep expertise in applying RL to complex tasks, agent-based modeling, or planning.
• Strong software engineering fundamentals and experience building robust, scalable systems in a production environment.
• Proven ability to translate cutting-edge research into practical, high-impact applications.
• M.S. or Ph.D. in Computer Science, Machine Learning, or a related quantitative field, or equivalent exceptional experience.

Preferred Qualifications

• A strong track record of publications in top-tier ML conferences (e.g., NeurIPS, ICML, ICLR, SIGIR, KDD, WebConf).
• Experience building and designing large-scale infrastructure for a \”new computing paradigm.\”
• Passion for tackling ambiguous, foundational research problems and reducing them to practice.
• Experience building or working with simulation environments and synthetic data generation.

Seniority level

• Mid-Senior level

Employment type

• Full-time

Job function

• Engineering and Information Technology
• Industries: Software Development

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London, England, United Kingdom

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