Machine Learning Engineer MF
il y a 1 mois
Since 2014 Wiremind has positioned itself as a technical company transforming the world of transport and events with a 360 approach combining UX software and AI.
Our expertise lies primarily in optimizing and marketing our clients capacity. We work on various projects such as ticket forecasting and pricing 3D optimization of air freight or scraping competitor prices. Our applications are the preferred tool of companies such as SNCF United Airlines Qatar Airways or even PSG to visualize analyze and optimize their capacity.
Dynamic and ambitious we strive to maintain our technical DNA which is the engine of our success. The company profitable and selffinanced since its creation 10 years ago is mainly composed of engineers and experts and currently supports the growth of our business model based on softwareasaservice solutions.
Your missionsAt Wiremind the Data Science team is responsible for the development monitoring and evolution of all MLpowered forecasting and optimization algorithms in use in our Revenue Management systems. Our algorithms are divided in 2 parts:
- A modelling of the unconstrained demand using ML models (e.g. deep learning boosted trees) trained on historical data in the form of timeseries
- Constrained optimizations problems solved using linear programming techniques
You will be joining a team shaped to have all profiles necessary to constitute an autonomous department (devops software and data engineering data science AIML operational research). There you will leverage stateoftheart AI/ML methods and ironclad validation processes to deliver robust interpretable prediction systems.
As a Machine Learning Engineer with support from a Lead ML you will take part in the development and improvement of new features and algorithms for our SaaS applications using a mixture of proven traditional modelbased methods as well as recent breakthroughs in Deep Learning for regression problems.
In practice even though there is no typical day you can expect to:
- Develop maintain and propose improvements for our training framework via Argo MLFlow
- Deploy and monitor of models in production
- Oversee implementations of new clients from the data analysis phase modeling deployment and hypersupervision of the first optimization runs in production
- Develop analytics and AB testing tools to help us continuously improving our models
- Backend: Python 3.11 with SQLAlchemy
- Orchestration: Argo workflows over an autoscaled Kubernetes cluster
- Datastores: Druid and postgresql
- Common ML libraries/tools: TensorFlow/Keras LightGBM XGBooost Pandas Dask Dash Jupyter notebooks
- Model versioning and registry tool: Mlflow
- Gitlab / Kubernetes for CI/CD
- Prometheus/Grafana and Kibana for operations
- You possess a Masters Degree in Data Science Applied Mathematics Computer Science or similar field with a first experience in Python or an equivalent backend language
- You have worked on at least one deep learning framework such as tensorflow or pytorch
- You have a pragmatic approach to ML where testing and frequent deliveries of small incremental gains supported by validation / alerting processes to avoid regression is preferred to a long tunneled research process
- Youre passionate about addressing business challenges through innovative technological solutions
- You are committed to maintaining highquality standards in all aspects of your work
- Experience modelling time series and/or price elasticity is a plus
By joining us you will integrate:
- A selffinanced startup with a strong technical identity
- Beautiful 700 m offices in the heart of Paris (Bd Poissonnire)
- 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
You will also benefit from:
- Training on demand
- A hybrid policy: 2 days of remote work per week and the possibility to work occasionally from abroad
- A great company culture (monthly afterworks regular meetings on technology and products annual offsite seminars teambuilding)
- An initial discussion with our Talent Acquisition Manager
- An interview with the Hiring Manager
- A technical test or case study to be prepared
- A last interview at our offices to discuss your technical test or case study and meet with members of the team
Wiremind is committed to equality of opportunity diversity and fairness. We encourage all candidates with the necessary experience to apply for our job offers.
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