Description review
Principal AI & Agent Systems Engineer (gn) @ Fusion Energy Venture, Munich
atlantic.vc · Remote job · back to the listing
HR standards
55/100
needs work
Title ↔ description
73/100
solid
Reads as
Machine Learning Engineer
90% confident
What this role officially is
data scientist — ESCO, the EU occupation classification
Data scientists find and interpret rich data sources, manage large amounts of data, merge data sources, ensure consistency of data-sets, and create visualisations to aid in understanding data. They build mathematical models using data, present and communicate data insights and findings to specialists and scientists in their team and if required, to a non-expert audience, and recommend ways to apply the data.
Also known as: data scientists, data engineer, research data scientist, data expert, data research scientist
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What the listing never says
- 25 bullet points. Long requirement lists deter qualified candidates, who read them as hard gates. Scope clarity
- No pay range published. Candidates cannot tell whether applying is worth their time. Pay transparency
The listing, marked up
Nothing in the wording of this listing tripped a check. The scores above still judge how complete and coherent it is.
This is an Atlantic portfolio venture.
About the Venture
We are building a new path to fusion energy. Every major leap in human civilisation has followed a breakthrough in energy, from fire to steam to electricity, and we believe fusion is the next one. Our bet is that it will not come from building bigger machines. It will come from controlling matter with enough precision that fusion becomes a manufacturable technology, atoms aligned exactly enough that fusion happens under controlled conditions, on a chip. This is a semiconductor-scale path to clean power, and our stance is precision over brute force. We start in physics and simulation, then build the physical proof.
About the Role
Reaching a chip-scale approach means working through physics and simulation at a depth that is hard to reach by conventional means, and to do that we need a new class of scientific intelligence. You will work directly with the founders to design that system from the ground up: an AI-driven research platform that can read papers, connect ideas across disciplines, orchestrate simulations, evaluate hypotheses and learn from results. This is not a chatbot or prompt engineering role, and we are not building a foundation model or competing with OpenAI, Anthropic or Google. We believe these systems will need richer representations than today's token-prediction models, so you will help explore new architectures for scientific reasoning, memory, hypothesis generation and autonomous discovery. The better that system works, the faster we get to the physical proof.
What you'll do
• Design multi-agent research systems and the orchestration that ties them together
• Build long-term memory architectures for scientific reasoning
• Create paper ingestion and knowledge extraction pipelines
• Develop scientific reasoning workflows and connect AI agents to simulation environments
• Build autonomous experiment and evaluation loops
• Design retrieval, planning and orchestration systems
• Integrate state-of-the-art LLMs and open-source models
• Develop scalable infrastructure for continuous learning
• Explore next-generation AI architectures for scientific discovery
About You
We care far more about what you have built than about formal credentials. You will thrive here if you enjoy solving problems nobody has solved before, learn quickly and independently, and are comfortable with uncertainty. This role suits someone who wants to help create a new category of scientific intelligence rather than optimise an existing product.
• You have already built real agent systems, with strong experience across several of: multi-agent architectures, tool use and function calling, agent orchestration, planning systems, long-term memory, knowledge graphs, autonomous research workflows, RAG architectures and evaluation frameworks
• You write production-quality software with strong Python skills, and you are comfortable with API design and integration
• You know your way around cloud infrastructure, Docker and containerisation, and databases including vector databases
• You are comfortable with the mathematical ideas this work draws on, such as linear algebra, optimisation, probability, graph theory and dynamical systems
• You do not need to be a theoretical physicist, but you should enjoy working on highly technical scientific problems
Nice to have:
• Physics simulations, scientific computing or computational physics
• HPC environments
• Reinforcement learning
• AI for Science
• Quantum computing
• Scientific publishing workflows
• Open-source AI frameworks
Why Join
• Our goal is bigger than software. The systems you build will be used to accelerate research in fusion energy, scientific discovery, advanced simulation, AI for physics and quantum technologies. Success here is measured in real scientific progress.
• Work with an exceptional founding team with scientific and commercial track records across places like LMU, Apple, Amazon, Eurazeo, Sprin-D and McKinsey. Around them is a small group of physicists, simulation experts and AI specialists who value curiosity, independent thinking and the courage to challenge assumptions.
• We are remote-first, so you can work from Munich, Berlin, London, Lisbon or wherever you do your best work. We keep bureaucracy to a minimum so talented people can move fast and follow promising ideas.
• This is a chance to help build something before it becomes obvious, and to help solve one of humanity's hardest problems.
Find more English Speaking Jobs in Germany on Arbeitnow
About the Venture
We are building a new path to fusion energy. Every major leap in human civilisation has followed a breakthrough in energy, from fire to steam to electricity, and we believe fusion is the next one. Our bet is that it will not come from building bigger machines. It will come from controlling matter with enough precision that fusion becomes a manufacturable technology, atoms aligned exactly enough that fusion happens under controlled conditions, on a chip. This is a semiconductor-scale path to clean power, and our stance is precision over brute force. We start in physics and simulation, then build the physical proof.
About the Role
Reaching a chip-scale approach means working through physics and simulation at a depth that is hard to reach by conventional means, and to do that we need a new class of scientific intelligence. You will work directly with the founders to design that system from the ground up: an AI-driven research platform that can read papers, connect ideas across disciplines, orchestrate simulations, evaluate hypotheses and learn from results. This is not a chatbot or prompt engineering role, and we are not building a foundation model or competing with OpenAI, Anthropic or Google. We believe these systems will need richer representations than today's token-prediction models, so you will help explore new architectures for scientific reasoning, memory, hypothesis generation and autonomous discovery. The better that system works, the faster we get to the physical proof.
What you'll do
• Design multi-agent research systems and the orchestration that ties them together
• Build long-term memory architectures for scientific reasoning
• Create paper ingestion and knowledge extraction pipelines
• Develop scientific reasoning workflows and connect AI agents to simulation environments
• Build autonomous experiment and evaluation loops
• Design retrieval, planning and orchestration systems
• Integrate state-of-the-art LLMs and open-source models
• Develop scalable infrastructure for continuous learning
• Explore next-generation AI architectures for scientific discovery
About You
We care far more about what you have built than about formal credentials. You will thrive here if you enjoy solving problems nobody has solved before, learn quickly and independently, and are comfortable with uncertainty. This role suits someone who wants to help create a new category of scientific intelligence rather than optimise an existing product.
• You have already built real agent systems, with strong experience across several of: multi-agent architectures, tool use and function calling, agent orchestration, planning systems, long-term memory, knowledge graphs, autonomous research workflows, RAG architectures and evaluation frameworks
• You write production-quality software with strong Python skills, and you are comfortable with API design and integration
• You know your way around cloud infrastructure, Docker and containerisation, and databases including vector databases
• You are comfortable with the mathematical ideas this work draws on, such as linear algebra, optimisation, probability, graph theory and dynamical systems
• You do not need to be a theoretical physicist, but you should enjoy working on highly technical scientific problems
Nice to have:
• Physics simulations, scientific computing or computational physics
• HPC environments
• Reinforcement learning
• AI for Science
• Quantum computing
• Scientific publishing workflows
• Open-source AI frameworks
Why Join
• Our goal is bigger than software. The systems you build will be used to accelerate research in fusion energy, scientific discovery, advanced simulation, AI for physics and quantum technologies. Success here is measured in real scientific progress.
• Work with an exceptional founding team with scientific and commercial track records across places like LMU, Apple, Amazon, Eurazeo, Sprin-D and McKinsey. Around them is a small group of physicists, simulation experts and AI specialists who value curiosity, independent thinking and the courage to challenge assumptions.
• We are remote-first, so you can work from Munich, Berlin, London, Lisbon or wherever you do your best work. We keep bureaucracy to a minimum so talented people can move fast and follow promising ideas.
• This is a chance to help build something before it becomes obvious, and to help solve one of humanity's hardest problems.
Find more English Speaking Jobs in Germany on Arbeitnow