Senior ML Engineer

TL;DR

Senior ML Engineer (Machine Learning): Own the architectural blueprint and technical direction of key components in an ML stack for optimizing the quantum chip lifecycle with an accent on scalable, maintainable, and observable production ML workflows. Focus on translating physical constraints into algorithmic requirements, driving multi-quarter improvements in the ML stack, and leading engineering standards through mentorship and cross-team design reviews.

Location: Paris

Company

hirify.global develops a universal, fault-tolerant quantum computer based on superconducting cat qubits.

What you will do

• Design and implement complex ML workflows, ensuring solutions are scalable, maintainable, and observable in production.
• Collaborate with quantum physicists to identify chip-lifecycle bottlenecks and translate physical constraints into precise algorithmic requirements.
• Own the technical roadmap for one or more core optimization components by scoping and prioritizing multi-quarter ML stack improvements.
• Lead engineering quality through code reviews, mentorship of junior engineers, and defining “gold standard” software design patterns.
• Influence ML engineering practices beyond the immediate team by participating in cross-team design reviews and defining reusable patterns.

Requirements

• 5+ years of industry experience in Machine Learning Engineering or Software Engineering with a strong ML focus, or a PhD + 3 years in industry.
• Proven track record owning an ML project end-to-end, from ambiguous problem definition through production deployment and iteration.
• Advanced Python expertise and modern ML stack experience (PyTorch/JAX), plus experience building production-grade software (not only notebooks).
• Experience with MLOps tools, distributed training, or cloud infrastructure.
• Strong mathematical fluency in linear algebra and optimization, with ability to discuss technical trade-offs with research scientists.

Nice to have

• Experience in hardware-constrained environments (robotics, semiconductors, physics) or scientific computing.
• Research impact such as lead authorship at top-tier ML conferences, or a background in Physics/Quantum mechanics.

Culture & Benefits

• Flexible remote policy up to 40% per month.
• BSPCE plan with direct IP compensation via substantial bonuses for driving core patents.
• 25-day vacation policy (as per French law) plus RTT, and parental plan support including crèche support and additional days off for children under 12.
• Competitive health coverage (Alan), meal vouchers (Swile), and transportation cost coverage (as per French law) or yearly bicycle allowance.
• Subsidized Urban Sports Club membership and mental health support (moka.care).
• French language courses covered by the company.

Hiring process

• Screening call (30 min) with Talent Acquisition.
• Interviews: Hiring Manager (45 min), Technical interview (90 min), Leadership team interview (30 min), Fit interview (45 min), then reference check.