2 weeks ago

Applied AI/ML Engineer (Agents)

CuspAI

Amsterdam

2 weeks ago

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CuspAI is seeking an experienced Applied AI/ML Engineer (Agents) to design and build intelligent agents for our autonomous materials discovery engine. The role involves developing agentic frameworks, experimental design, and interdisciplinary collaboration with chemists and materials scientists. Ideal candidates have strong ML and software engineering skills, with experience in PyTorch or JAX, and a passion for solving global sustainability challenges.

Core AIHybridFull-timeMid LevelPyTorchJAX

Applied AI/ML Engineer (Agents)

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Core AIHybridFull-timeMid LevelPyTorch

Salary

Not specified

Work Location

Amsterdam, North Holland, Netherlands, NL

Work Model

Remote (with expectation to be in office three days per week in Cambridge, London, Amsterdam, or Berlin)

Experience Required

5 years

Employment Type

Full-time

Experience Level

PhD or Masters degree and 4-5 yrs industry experience (or PhD with slightly less experience)

Core Qualifications

Technical (Must-have)

PyTorchJAXMachine LearningSoftware EngineeringCI/CDMLOpsLLM-assisted programmingAgentic frameworksBayesian optimizationActive learningSequential decision-makingMaterials scienceChemistry

Soft Skills

Proactive builder mentalityBias toward shipping and iterationWillingness to learnInterdisciplinary collaborationCommunication

Preferred Qualifications

Technical (Nice-to-have)

Materials scienceChemistryDrug discoveryAgentic frameworksLLM-powered applicationsReinforcement learningPlanning modelsSelf-improving systemsMulti-tool agentsRLHFRLAIF

Key Responsibilities

•Design the agentic framework that powers our platform to discover new materials
•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
•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
•Build agents that perform experimental design using Bayesian optimization, active learning, or related methods
•Help close the loop between simulation and physical experiments
•Develop strategies for multi-fidelity and multi-objective decision-making
•Work closely with Chemists, Materials Scientists, and the rest of the Agent team
•Work on customer projects and implement the direct needs required for these projects

AIMachine LearningAgentsMaterials ScienceRemoteFull-timeEngineeringTechnology

Core Qualifications

Technical (Must-have)

PyTorchJAXMachine LearningSoftware EngineeringCI/CDMLOpsLLM-assisted programmingAgentic frameworksBayesian optimizationActive learningSequential decision-makingMaterials scienceChemistry

Soft Skills

Proactive builder mentalityBias toward shipping and iterationWillingness to learnInterdisciplinary collaborationCommunication

Key Responsibilities

•Design the agentic framework that powers our platform to discover new materials

•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

•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

•Build agents that perform experimental design using Bayesian optimization, active learning, or related methods

•Help close the loop between simulation and physical experiments

•Develop strategies for multi-fidelity and multi-objective decision-making

•Work closely with Chemists, Materials Scientists, and the rest of the Agent team

•Work on customer projects and implement the direct needs required for these projects