Senior Deep Learning Scientist – Acoustic

Jobtailor; Paris; Sur place; EUR 70 000 - 110 000; Plein temps

Résumé du poste

Jobtailor is seeking an experienced Machine Learning/Signal Processing engineer in Paris, France, to develop, train and deploy Deep Learning models for client projects. You will translate client needs into technical objectives, contribute to novel data types and drive scalable MLOps tooling.

The role emphasizes production-grade software, collaboration with sales for scoping, and mentoring junior team members while traveling to client sites periodically.

Qualifications

• Master’s degree in Software Engineering, Computer Science, Deep Learning, Computer Vision or Acoustic Processing.
• 6+ years of professional experience in acoustic or electromagnetic signal processing.
• Experience putting software solutions into production, ideally on-prem (deployment, monitoring, observability).
• Strong knowledge of Python and software development best practices.
• Good understanding of databases, orchestration and containerization.
• Experience with agile development.

Responsabilités

• Develop, train and test Deep Learning or signal-processing models for client delivery.
• Translate client needs into technical objectives and propose suitable solutions.
• Contribute to low-TRL projects on new data types.
• Ensure maintainability and scalability of MLOps tools and workflows.
• Propose innovative approaches to improve detectors and development efficiency.
• Mentor junior team members and share best practices.
• Participate with sales in upstream scoping and estimations.
• Travel to client sites 2–4 days per month to deploy tools.

Connaissances

Python

Agile development

Communication

End-user mindset

Formation

Master’s degree in Software Engineering, Computer Science, Deep Learning, Computer Vision or Acoustic Processing

Outils

Docker

Kubernetes

Databases

Description du poste

Responsibilities

• Develop, train and test Deep Learning or signal‑processing models that will be delivered to the client
• Participate in upstream scoping to translate the client’s operational needs into technical objectives, proposing the solutions best suited to the challenges posed by the data or specific contexts
• Contribute to low‑TRL projects on new data types to address emerging problems
• Ensure the maintainability and scalability of the various components of our MLOps tools that improve team productivity, including conducting periodic technology watch and proposing evolutions of the team’s technical vision
• Propose creative and innovative approaches to improve the performance of delivered detectors and the efficiency of our development work
• Mentor more junior team members by sharing your technical expertise and disseminating best practices
• Occasionally participate with the sales teams in the upstream scoping/estimations of a technical project
• Regularly travel to client sites, on average two to four days per month, to deploy our tools on target data

Requirements

• Master’s degree or equivalent in Software Engineering, Computer Science, Deep Learning, Computer Vision or Acoustic Processing
• More than 6 years of professional experience in acoustic or electromagnetic signal processing
• Experience putting software solutions into production, ideally on‑prem (deployment, monitoring, observability)
• Strong knowledge of Python and software development best practices
• Good understanding of databases, orchestration and containerization
• Experience with agile development without applying it dogmatically
• Ability to communicate and defend a technical vision, with pedagogical skills, synthesis and guidance
• User‑centric mindset, prioritizing the needs of end users
• Openness, strong communication skills and a collaborative team spirit

Core Competencies

Demonstrates expertise in developing and deploying Deep Learning and signal‑processing models, with a strong focus on maintainability and scalability of MLOps tools. Possesses a user‑centric mindset and effective communication skills to translate technical objectives and mentor team members.