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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Quantum Solutions Engineer - Scientific Machine Learning M/W - **Company:** PASQAL USA INC. - **Location:** Chicago, IL, United States - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Artificial Neural Networks, Emulators, Experimental Data, Machine Learning, Quantum Computing, Machine Learning Operations - **Published:** August 4, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=649fc4b2fd3339a7 ## About the Role * Master's degree or PhD in Machine Learning, Computational Chemistry or Quantum Physics * 2+ years of experience in a similar role * Strong ML engineering background, including model training and evaluation, classical baselines, metrics, and reproducible experimentation. * Hands-on experience with graph-structured data and Graph Machine Learning, such as graph kernels, Graph Neural Networks, or graph representations. * Familiarity with quantum computing or quantum mechanics concepts and constraints, including the differences between classical simulation, emulation, and hardware execution. * Working knowledge of fundamental chemistry concepts and familiarity with molecular representations such as descriptors, fingerprints, molecular graphs, or SMILES. * Strong interest in applying quantum computing to practical machine learning and scientific problems. * Experience working with molecular, chemical, materials, or other scientific data. * Ability to build end-to-end ML pipelines (pre/post-processing, integration with existing tools/platforms). * Physics background (quantum/atomic/optics) is a plus. * Delivery mindset and ownership (client-facing deliverables, pragmatism, trade-offs). * Strong communication and collaboration with internal R&D, hardware, and platform teams. Right to work in USA without sponsorship is preferred. ## Description We are looking for a Quantum Solutions Engineer to join our Quantum Applications department and build client-facing solutions based on PASQAL's quantum algorithm portfolio. This application-driven engineering role focuses on adapting, integrating, and validating quantum and quantum-enhanced machine learning methods for real-world partner and client use-cases, with a strong focus on molecular and chemical applications. The goal is to turn PASQAL's existing methods into reliable client deliverables by combining scientific machine learning, Graph Machine Learning, and analog quantum computing. Contributions to internal method improvement are welcome when they directly support project outcomes. You will join as a Scientific Machine Learning Engineer specializing in chemistry applications, working at the interface between graph machine learning, quantum algorithms, and industrial use cases. With strong engineering skills and an interest in quantum computing (physics background is a plus), you will: * Adapt and implement PASQAL's existing quantum and quantum-enhanced Graph ML algorithms for client datasets, scientific constraints, and performance targets. * Translate scientific and chemical use cases into well-defined machine learning tasks, such as molecular property prediction, classification, ranking, or candidate screening. * Select and implement suitable representations for molecules and chemical systems, including physicochemical descriptors, fingerprints, molecular graphs, and quantum feature representations. * Integrate ML pipelines with quantum execution workflows, emulation and simulation platforms, PASQAL QPUs, and internal tooling. * Collaborate closely with internal R&D teams to transfer quantum methods from research to application, clarify their assumptions and limitations, and select the most appropriate approach from PASQAL's portfolio. * Work closely with chemistry experts from clients and partners to understand the scientific meaning, quality, and limitations of molecular and experimental data. * Produce maintainable code, technical documentation, benchmark reports, and handover material so delivered solutions can be reproduced, reused, and supported. * Maintain an active scientific and technological watch in Quantum Machine Learning, Graph Machine Learning, and molecular machine learning. ## Related Videos - [Introduction to Azure Machine Learning](https://www.wearedevelopers.com/videos/368-introduction-to-azure-machine-learning) - [DevOps for Machine Learning](https://www.wearedevelopers.com/videos/179-devops-for-machine-learning) - [Quantum DevOps - Quantum Application Development](https://www.wearedevelopers.com/videos/1441-quantum-devops-quantum-application-development) - [Thinking Differently - How to Make Money from Cyber Attacks & Cheats](https://www.wearedevelopers.com/videos/745-thinking-differently-how-to-make-money-from-cyber-attacks-cheats) - [Empowering Retail Through Applied Machine Learning](https://www.wearedevelopers.com/videos/976-empowering-retail-through-applied-machine-learning) - [Effective Machine Learning - Managing Complexity with MLOps](https://www.wearedevelopers.com/videos/185-effective-machine-learning-managing-complexity-with-mlops) ## Related Articles - [7 Cloud Computing Trends Coming in 2025 for Developers](https://www.wearedevelopers.com/magazine/412-7-cloud-computing-trends-coming-in-2025-for-developers) - [The Fastest-Growing Tech Sectors to Look Out for in 2025](https://www.wearedevelopers.com/magazine/373-the-fastest-growing-tech-sectors-to-look-out-for-in-2025) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [Welcome to Switzerland](https://www.wearedevelopers.com/magazine/4-welcome-to-switzerland) - [Best Coding Boot Camps in Germany](https://www.wearedevelopers.com/magazine/237-best-coding-boot-camps-in-germany)