Software Engineer - Machine Learning

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

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• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

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Learning budget

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Salary

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Market context

U.S. role benchmark (BLS OEWS)

$116,543 U.S. median for this role

Projected growth (BLS Employment Projections)

+9.8% - Much faster than average

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Engineering From the posting source checked Jun 20, 2026

Seniority

Mid From the posting source checked Jun 20, 2026

Schedule

Shift type

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Weekend work

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Application

Cover letter

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Assessment

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Deadline

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Where they hire

State eligibility is not yet verified.

About this role

Software Engineer - Machine Learning Paris Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology, and trading expertise has shaped our collaborative mindset, which enables us to solve the most complex challenges. QRT's culture of innovation continuously drives our ambition to deliver high quality returns for our investors. As a Software Engineer - ML you will focus on turning research outputs into robust, scalable, and well-operated production systems. You will directly contribute to our engineering platform and automation efforts that accelerate delivery, improve reliability, and raise the quality bar across the ML and research lifecycle. Your future role within QRT: - Collaborate closely with Research and Machine Learning engineers to transition prototypes into production-grade services, jobs, and pipelines. - Design, implement, maintain and support end-to-end research-to-production workflows (data/feature pipelines, training/inference jobs, batch processes, internal tooling). - Build and improve automation around packaging, configuration, and environment reproducibility. - Develop and maintain CI/CD pipelines to enforce code quality, testing, security checks, and smooth deployments. - Contribute to deployment and runtime operations (containers, orchestration, infrastructure integration), ensuring reliability, performance, and maintainability. - Implement monitoring, alerting, and observability (logs/metrics/traces) for production workloads; define operational runbooks and on-call support procedures when needed. - Troubleshoot and resolve integration and production issues, ensuring optimal performance, robustness, and reliability. - Create and maintain detailed documentation of system

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