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

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

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

Lead Machine Learning Engineer, CDI

Key skills