Mlops Engineer

Location

Paris, France

**Who we are?**

Besedo is a fast-growing tech company offering content moderation tools and services to online marketplaces around the world. Every year, we review and moderate over 500 million pieces of user-generated content and block 40 million fraud attempts.

Besedo has headquarters in Stockholm (Sweden) and employs over 400 employees in 6 offices in different continents. Implio is our all-in-one SaaS moderation platform that combines state-of-the-art AI (deep learning, NLP, computer vision) with a powerful user interface for human moderation and statistics. The result is an easy-to-use content moderation solution that leads classified, dating and sharing economy sites from all around the world to love and trust.

Learn more about Implio in this video, and about Besedo on our website.

Come and make the internet better and safer with us

**Job description**

**About this position**
We also offer a flexible work arrangement that accommodates a hybrid schedule, allowing you to balance your time effectively between home and our office. You will work with a team of talented Machine Learning Engineer DevOps and Developer who are passionate about their work and like to have fun in the
process.

**Your mission**
As an MLOps Engineer and a member of the Data Science team, you will play a pivotal role in shaping our machine learning lifecycle. You will be engaged in an array of daily tasks that involve:

- Collaborating with Data Scientists to convert experimental models into scalable production services, adopting practices such as A/B testing, Canary releases, and more
- Ensuring seamless and automated deployment of models using CI/CD pipelines
- Implementing monitoring solutions for models' performance, and designing fallback plans for retraining and redeployment
- Strategically managing resources (computational power and storage) to balance the performance of models, systems, and pipelines with costeffectiveness and efficiency
- Designing, building, and maintaining Machine Learning (ML) pipelines to facilitate ML workflows, from data acquisition and processing to model deployment and monitoring
- Implementing robust data validation strategies and methodologies to ensure data quality and reliability in ML models Staying updated with recent advances in MLOps, and identifying and implementing new technologies that can improve and optimize our machine learning system

You will be working in close collaboration with stakeholders: Data Scientists, DevOps, Front-end/Back-end Developers and Product Owner, to come up with the very best solutions.

**What it’s like working with us?**
At Besedo, we all come from different cultures and backgrounds, but we share a common set of values:

- We like to get things done ✔️ We support each other to reach our goals and grow as professionals We love to learn, share and have fun together
- We strive to offer a great work environment:

- Work from home friendly (office space is also available in Paris)
- Choice of laptop and desk setup
- Great health insurance and benefits

**Preferred experience**
We are looking for someone having worked for 3+ years or more as an MLOps, Engineer or in a related field and who has the following experience and skills:

- Proficiency in Python, and a strong understanding of Machine Learning libraries and frameworks such as PyTorch (preferred)
- Demonstrable experience with data structures, algorithms, and software design
- Hands-on experience with building, deploying, and maintaining machine learning models in a production environment
- Practical knowledge of containerization technologies (Docker) and orchestration systems (Kubernetes)
- Familiarity with CI/CD tools and version control systems (Git)

As a person, you are:

- Passionate about solving problems in an elegant and principled manner
- Enthusiast about team work, learning and teaching
- Detail-oriented, outgoing and a good communicator
- Fluent in English (French is not mandatory)

Extra points if you have experience with:

- Proficiency in Distributed Computing on different environments and cloud platforms (AWS, GCP, Azure)
- Experience with Workflow Orchestration tools, such as Prefect or Airflow