Designing, developing, and implementing machine learning models and algorithms at PayPal. Collaborating with data scientists and software engineers to enhance services through innovative AI/ML solutions.
About the role
- Lead Machine Learning Engineer managing ML Ops and technical leadership at Wiremind, a transport technology company optimizing capacity for clients like SNCF and United Airlines.
Responsibilities
- Own and improve the ML Ops roadmap for our training, deployment, monitoring, and retraining workflows
- Lead, mentor, and raise the bar for more junior team members by reviewing designs and code, sharing best practices, and helping the team grow in autonomy
- Structure execution and delivery by helping define priorities, turning roadmap objectives into actionable plans, and ensuring work is delivered with a high level of quality
- Oversee new client implementations from data analysis to modeling, deployment, and hyper-supervision of the first optimization runs in production
- Improve our internal platform and tooling so that pipeline components are reusable, robust, and usable across the entire team
- Collaborate closely with Product, R&D, Data Engineering, and other stakeholders to translate business needs into scalable ML systems and features
- Act as a technical lead and organizational reference point within your squad and, more broadly, within Wiremind
Requirements
- You hold a Master’s degree in Data Science, Applied Mathematics, or Computer Science
- At least 5 years of experience in Data Science, ML Engineering, or a similar backend role applied to ML systems
- Managed a team
- Strong technical background and master the full lifecycle of a machine learning project, from experimentation to production operations
- Strong knowledge of ML Ops concepts, including deployment, monitoring, reproducibility, and production reliability
- Experience mentoring or leading other team members
- Comfortable helping structure a team's work and raising its level of execution
- Pragmatic and result-oriented approach to ML: testing and frequent deliveries of incremental gains are preferred to long tunneled research processes
- Enjoy mentoring junior colleagues and supporting their professional growth
- Experience modeling time series and/or price elasticity is a plus
Benefits
- A self-financed startup with a strong technical identity!
- Beautiful 900 m² offices in the heart of Paris (Bd Poissonnière)
- Attractive remuneration indexed on performance
- A caring and stimulating team that encourages skills development through initiative and autonomy
- A learning environment with opportunities for evolution
- Training on demand
- A hybrid policy: 2 days of remote work per week and the possibility to work occasionally from abroad
- Access to WellPass at a preferential rate to maintain your well-being
- A great company culture (monthly afterworks, regular meetings on technology and products, annual off-site seminars, team-building…)
- An annual budget for your IT equipment
- A partnership with the People & Baby network of inter-company nurseries to help with childcare for children aged 0 to 3
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
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