Meet Arago and the Aragonians
Arago is an AI and computer hardware company whose mission is to drive the course of history forward. We do so by accelerating breakthroughs at the intersection of AI and semiconductors.
Founded in 2024 by AI researchers and physicists with deep expertise in photonics, electronics, software, mathematics, and machine learning, Arago brings together a lean team of engineers and scientists from the world’s top companies and research labs.
Composed of nine nationalities and operating from hubs in France, North America, and Israel, we believe in great science and fast achievements. Our work is guided by these core principles:
Do great things: we deliver work we’re proud to sign our name to.
High velocity: speed matters. We move quickly, one step at a time.
One unit: we’re all in this together, with relationships grounded in trust, respect, and camaraderie.
Arago is backed by executives from Apple, Arm, Nvidia, Microsoft, and Hugging Face, as well as prominent US and European deeptech venture firms and exited founders.
What you’ll do
Develop and optimize advanced manufacturing and packaging processes by combining physical experimentation, simulation, and data-driven modeling to enable scalable, high-yield production of complex optoelectronic systems.
Responsibilities
Design, model, and validate advanced manufacturing, packaging, and assembly processes using a combination of physical experimentation, simulation, and data-driven analysis. This includes developing digital twins, statistical models, and physical simulations to optimize process parameters and predict performance.
Drive process development from lab-scale prototyping to production readiness, focusing on scalability, yield, and manufacturability. This involves hands-on experimentation, tool setup, metrology, and collaboration with design and integration teams to ensure process-device alignment.
Implement and refine advanced yield estimation and defect analysis techniques, integrating process monitoring data with predictive models to identify failure modes and improve process robustness.
Contribute to continuous improvement of internal methodologies by documenting process flows, simulation frameworks, and validation protocols, enabling reproducibility and knowledge transfer.
Required Skills and Experience
Strong background in applied mathematics, statistics, and computational modeling, with proficiency in Python, MATLAB, or similar tools for process simulation, data analysis, and automation.
Experience with digital twin development, process modeling, or statistical process control in a manufacturing or R&D setting is highly valued.
Familiarity with advanced manufacturing or packaging techniques used in precision manufacturing or semiconductor process engineering, with exposure to industrial-scale production environments.
Understanding of physical process principles such as thermal, mechanical, or chemical behavior in micro- and nano-scale systems, specifically as applicable to lithography, etching, bonding, assembly, or packaging in electronic, photonic, or MEMS contexts.
Comfortable working hands-on in lab or pilot-line environments, with a detail-oriented and methodical approach.
Effective communicator able to collaborate with design, integration, and production teams to close the loop between simulation and physical implementation.
Pay and benefits
Competitive cash compensation, with final package based on location, experience, and the pay of team members in similar positions.
Meaningful stock option plan offered at the earliest stage of the company (included in the majority of full time offers).
Relocation bonus and coverage of moving expenses for relocation within 20 minutes of the company’s location.
Healthcare coverage (including family-friendly options), pension contributions, professional development support, and 25 days of PTO, in addition to public holidays.
Ownership of a key technical domain, with significant vertical and/or horizontal growth opportunities, based on performance and individual drive.
A high-paced, multicultural (with 9 nationalities), and engineering-led environment.
