Make a huge impact at Dailymotion by joining our team as an MLOps Engineer.  

You will play a crucial role in bridging the gap between machine learning and engineering. Collaborating with the teams to deliver innovative and high-quality data products. You will be responsible for: 

Empowering ML Engineers by providing tools and infrastructure that enhance their productivity while adapting to their specific needs. 

Accelerating time-to-market for the first production-ready versions of ML products by ensuring seamless integration, proper service connections, and access to data and resources. 

Ensuring ML Engineers maintain control over their models in production, allowing them to monitor, troubleshoot, iterate quickly, and refine models and feature engineering logic. 

Facilitating large-scale ML experimentation by providing robust, reproducible, and scalable test environments for data science projects, enabling both qualitative experimentation (internal tests and demos) and quantitative experimentation (A/B testing in production). 

Owning the industrialization and deployment (CI/CD) of ML models, ensuring their reliability, scalability, and performance through advanced MLOps practices. 

Managing model operations and maintenance, guaranteeing optimal performance, monitoring, and continuous improvements in production. 

Dailymotion is proud to be an equal employment opportunity and affirmative action employer. We value inclusion and we want you to help us thrive for a more diverse community.

All our job offers are open to people with disabilities or impairments, and we actively encourage everyone to apply. If you have any accessibility needs or require any accommodations for the hiring process, please let us know in advance so that we can make any necessary arrangements.

• Location: Issy-Les-Moulineaux - Full remote

• Start Date: Asap

• Contract Type: CDI

🔍Want to learn more about us:

• Dailymotion.com

• New-York office - BuiltIn

• Offices in France - Welcome to the Jungle

• Our articles  

For the France offices :

🏡 Remote friendly, ability to work 3 months abroad

💰 Saving Plan Canal +

🍼  Paternity leave or Coparental leave extended 

🕶️  Living Employee Culture (Events/Trainings/Parties/All hands,…) 

🚀  Career development support (training/internal mobility/compensation cycle/360 feedback review …)

🏥  High-end Health Insurance and Personal Services Vouchers (CESU)

⛱️  Paid Time off – RTT and Saving time plan (CET)

✅  Meal Vouchers – Public Transport and Bike refund 

🎡 European Economic and Social Committee (sport membership/cinemas vouchers/gift vouchers/discount) 

⚽  Fitness Subscription thanks to our partnership with Gymlib

- 3+ years of experience in MLOps, DevOps, or Data Engineering. 

- Strong Expertise with cloud platforms (GCP,AWS,Azure) their ML services (Vertex AI, SageMaker, etc.) and data services ( Bigquery, buckets )  

- Strong Expertise in CD pipelines for ML models (Flux) 

- Experience  in ML Orchestrators ( Kubeflow, Kuberay )  

- Experience  in CI pipelines for ML models (Flux, Jx3) 

- Experience in Data pipelines for ML models (Airflow,DataFlow,Kestra) 

- Experience with Data lifecycle Management  (Storage policies, costs optimization , security, encryption). 

- Proficiency in containerization and orchestration (Docker, Kubernetes, Helm). 

- Experience in ML infrastructure optimization  (GPUs,TPUs, Inferentia). 

- Expertise with Infrastructure as Code (Terraform). 

- Expertise in monitoring and observability capabilities (Prometheus, Datadog, Looker) 

- Strong programming skills in Python, with experience in Bash scripting; knowledge of Go or Rust is a plus. 

Soft Skills 

- Strong collaboration and communication skills to work effectively with ML Engineers and cross-functional teams. 

- Ability to drive innovation and advocate for best MLOps practices within the company. 

- Cultural Alignment: We seek a creative, motivated individual who values growth and is eager to contribute to our team and product 

- Excellent English communication skills, capable of working effectively in an international team.