AI/ML Scientist — Quantization & Numerical Robustness

Arago; Paris; Sur place; EUR 90 000 - 150 000; Plein temps

Avantages offerts par ce poste

Stock options

Relocation support

Healthcare coverage

PTO 25 days + holidays

Professional development support

Transport subsidy 50%

Dynamic, multicultural engineering-led

Résumé du poste

Arago, an AI and hardware company, is seeking a research specialist to study how reduced precision and hardware non-idealities affect AI models and to develop quantization and robustness techniques for Arago's accelerator.

The role combines model research, numerical analysis, and hardware-software co-design, requiring deep expertise in ML quantization, numerical methods, and accelerator architectures, with strong Python/PyTorch skills and excellent English proficiency.

Qualifications

• Strong foundations in numerical methods, probability and statistics.
• Deep experience with ML quantization: PTQ, QAT, low-bit formats.
• Experience studying impact of precision/noise on model accuracy.
• Understands LLMs, diffusion/multimodal models and world models.
• Ability to design large-scale experiments and analyze robustness.
• Knowledge of accelerator architecture and hardware-software co-design.
• Strong Python/PyTorch skills; experience with research prototypes is a plus.
• Proficient English; French is a plus.

Responsabilités

• Design and run large-scale experiments to characterize model sensitivity to analog noise and non-idealities.
• Develop and validate numerical and noise models of hardware behavior.
• Research and implement quantization approaches across training, fine-tuning, post-training, and runtime.
• Identify precision requirements and advise hardware/software teams.
• Optimize trade-offs between model quality, robustness, and inference performance.
• Collaborate with hardware, compiler, runtime, and inference teams to translate findings into the software stack.

Connaissances

Mathematics

Physics

Computer Science

ML quantization

Numerical analysis

LLMs / diffusion models

Python / PyTorch

English proficiency

Formation

Quantitative degree

Outils

Custom operators

Simulators

Accelerator stacks

Description du poste

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:

1. Do great things: we deliver work we’re proud to sign our name to.

2. High velocity: speed matters. We move quickly, one step at a time.

3. 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

Research how reduced precision, analog noise, and other hardware non-idealities affect modern AI models, and develop quantization and robustness techniques tailored to Arago's custom AI accelerator. The role sits at the intersection of model research, numerical analysis, and hardware/software co-design.

Required Skills and Experience

• Strong background in mathematics, physics, computer science, or a related quantitative field, with solid foundations in numerical methods, probability, and statistics.

• Deep experience with ML quantization techniques, including PTQ, QAT, quantization-aware fine-tuning, mixed precision, and low-bit weight/activation formats.

• Experience studying the impact of numerical precision, approximation, perturbations, or hardware noise on model accuracy and stability.

• Strong understanding of modern model architectures, including LLMs, diffusion models, multimodal/video models, and/or world models.

• Ability to design rigorous, large-scale experiments and analyze accuracy/robustness trade-offs across models, layers, operators, and numerical formats.

• Good understanding of accelerator architecture, inference performance, memory/computation trade-offs, and the interaction between model-level techniques and hardware efficiency.

• Strong Python/PyTorch skills; experience with custom operators, simulators, emerging accelerator stacks, or research prototypes is a strong plus.

• Language: English at a proficient level. French is a plus.

Responsibilities

• Design and run large-scale experiments to characterize model sensitivity to analog noise, reduced precision, and other non-idealities of Arago's accelerator.

• Develop and validate numerical and noise models representative of hardware behavior.

• Research and implement quantization approaches spanning training, fine-tuning, post-training, and runtime/on-the-fly techniques.

• Identify model-, layer-, and operator-level precision requirements and provide recommendations to Arago's hardware and software teams.

• Optimize the trade-off between model quality, numerical robustness, and inference performance.

• Work closely with hardware, compiler, runtime, and inference teams to translate research findings into capabilities of Arago's evolving software stack.

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.

• Reimbursement of 50% of the public transport subscription fee.

• A high-paced, multicultural (with 10 nationalities), and engineering-led environment.

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