Applied AI/ML Engineer (Agents)
Cusp AI is hiring an Applied AI/ML Engineer (Agents) in Amsterdam, Netherlands. Level rates it ; you can apply on Cusp AI.
Level's read on this job
- On Level's scale, this machine learning engineer role is Builds AI ●●●●: the job is building AI systems.
- Some of the work can be done remotely, according to the posting.
- The posting mentions PyTorch, JAX and Python among its tools and skills.
- Level classes it as a senior role.
- Cusp AI has 23 other open roles on Level.
AI in this role
Design and build intelligent agentic systems and workflows to power an autonomous materials discovery platform.
About CuspAI
CuspAI is the frontier AI company on a mission to solve the breakthrough materials needed to power human progress. While nature took billions of years to perfect molecules, we are harnessing AI to unlock trillion-dollar materials breakthroughs in months, not millennia. Our founding team is the most cited in the world, comprised of world-class researchers in AI, chemistry and engineering.
We are working on some of the hardest and most important challenges including energy, clean water, the future of compute, and carbon capture, and this is just the start of what our 'search engine' for next-generation materials will unlock.
We invite you to be part of a diverse, innovative team at the intersection of AI and materials science, working to create impactful partnerships that drive innovation, scalability, and industry collaboration. This work matters. Your work matters.
We’re on the cusp of the on-demand materials era. Join us.
The Role
Due to rapid growth in our core AI capabilities, we are seeking an experienced Applied AI/ML Engineer (Agents) to design and build the intelligent agents that power our autonomous materials discovery engine.
Your Impact
You will be instrumental in developing the "artificial brain" of our agentic materials discovery engine. This is responsible for orchestrating complex, closed-loop scientific workflows, autonomously making decisions, running simulations, and driving experimental campaigns to find breakthrough materials faster than ever before.
Your work will directly accelerate CuspAI’s path to finding solutions for global sustainability challenges.
What You Will Do
Agentic systems
Design the agentic framework that powers our platform to discover new materials. This includes spanning dynamic, multi-stage simulation workflows from literature-grounded hypothesis generation through to computational and experimental validation
Build the integration that connects agents to ML models, simulation engines, databases, and heterogeneous compute backends
Design pipelines that let agents autonomously plan, schedule, execute, and interpret computational tasks at scale and over long periods of time
Use expert annotations from the Chemistry team to drive targeted improvements in agent planning, retrieval, and decision-making
Create evaluations to measure the effectiveness of agents
Experimental design
Build agents that perform experimental design — applying Bayesian optimization, active learning, or related sequential decision-making methods to decide what to compute or measure next, and to balance exploration and exploitation across long-running discovery campaigns
Help close the loop between simulation and physical experiments so that outcomes become durable knowledge — feeding back into what agents know and how their models reason — compounding across campaigns.
Develop strategies for multi-fidelity and multi-objective decision-making, where agents must trade off cost, time, and uncertainty across simulations and physical experiments
Interdisciplinary Collaboration
Work closely with Chemists, Materials Scientists, and the rest of the Agent team to co-develop our core orchestration intelligence
Work on customer projects and implement the direct needs required for these projects
Must Have Skills and Qualifications:
You are someone who gets excited about the opportunity to enable scientists to work on world changing challenges in this domain, with a personal interest in the potential applications of the technology that CuspAI is building.
Proficiency in the modern ML ecosystem such as PyTorch or JAX, with experience taking ML-driven systems from prototype to production
Strong software engineering skills (building systems at scale in a production environment): testing, modular design, CI/CD, and scalable ML operations in production environments
If you have a PhD or Masters degree and 4-5 yrs industry experience this would be ideal, but we will also consider you if you have a PhD and slightly less experience in industry
You have a proactive builder mentality with a bias toward shipping and iteration
Willingness to learn about materials science, and in particular experimental chemistry - to learn the vocabulary of the discipline to meaningfully interact with other stakeholders
Experienced in LLM-assisted programming, knowing its strengths and weaknesses thoroughly.
Bonus Points (But Not Critical):
Experience applying ML models specifically for materials science, chemistry, or drug discovery applications
Experience with agentic frameworks and building LLM-powered applications
Experience with sequential decision-making methods — Bayesian optimization, active learning, bandits, or reinforcement learning — applied to real-world systems
Advanced agentic-reasoning techniques: planning models, self-improving systems, multi-tool agents, or RLHF/RLAIF workflows
Additional Considerations
This role could be based in our Cambridge, London, Amsterdam or Berlin offices, with the expectation of being in the office three days per week. Additionally, there may be regular travel required to our other offices for collaboration and project oversight.
Join us in shaping the future of materials with AI. Together, we can create groundbreaking solutions for a more sustainable world.
What We Offer
A competitive salary: We value and reward impact and growth
Equity in CuspAI: You have a stake in the success of the company
Time off to stay fresh: 28 days holiday (DE, NL, UK) or 21 days holiday (JP, SG, US), in addition to local public holidays
‘Gold Standard’ parental leave: 26 weeks (primary caregiver) and 12 weeks (secondary caregiver) at full pay - we look after you and your family while we work on the most important materials discovery problems together
Professional development budget: We invest in your career development so you can stay up to date with the latest industry knowledge or add to your skills to increase impact and growth
Solve meaningful problems: See how your work has a direct impact on advancing materials science and solving sustainability and climate-related problems through the creation and application of bleeding-edge SOTA technology and revolutionary techniques
True interdisciplinary teamwork: Be part of a deeply collaborative environment bridging AI research, computational chemistry, and experimental science - work with world-class researchers and engineers who enjoy sharing knowledge and supporting each other
Join us in shaping the future of materials with AI. Together, we can create groundbreaking solutions for a more sustainable world.
CuspAI is an equal opportunities employer committed to building a diverse and inclusive workplace. We do not discriminate on the basis of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy or related condition (including breastfeeding), veteran status, or any other basis protected by applicable law.
We actively encourage applications from all backgrounds and value the unique perspectives and contributions that diversity brings to our team.
Please let us know if you require any specific adjustments during or after the interview process. We will do everything we can within reason to accommodate.
How we rate this
Applied AI/ML Engineer (Agents) at Cusp AI rates 95 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in machine learning engineer jobs at this level
Pay
- Typical machine learning engineer job
- $197k
This posting doesn't list pay. Use the typical machine learning engineer figure when pay comes up. See machine learning engineer jobs
Questions you could be asked
- Tell me about a research question you investigated. What did you find?
- Tell me about a project where agentic systems was part of your work. What did you do?
- Tell me about a project where machine learning was part of your work. What did you do?
- Tell me about a project where simulation was part of your work. What did you do?
- Tell me about a project where active learning was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: AI Research, Agentic Systems, Machine learning, Simulation, and Active Learning. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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