Machine Learning Engineer (F/H/X)

Saint-Ouen, FR

Alstom

Leading the way to greener and smarter mobility worldwide, Alstom develops and markets integrated systems that provide the sustainable foundations for the future of transportation.

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Req ID:471875 

 

At Alstom, we understand transport networks and what moves people. From high-speed trains, metros, monorails, and trams, to turnkey systems, services, infrastructure, signalling and digital mobility, we offer our diverse customers the broadest portfolio in the industry. Every day, more than 80 000 colleagues lead the way to greener and smarter mobility worldwide, connecting cities as we reduce carbon and replace cars.

 

 

 

Machine Learning Engineer (F/H/X)

 

Alstom announces an opening for a Machine Learning Engineer in Saint Ouen sur Seine. This position supports Alstom Data Science and AI programs by developing, testing, validating, and industrializing data-driven solutions in the mobility domain. The primary goal of these programs is to develop, deploy, and maintain AI/ML software modules to improve customer performance and experience using existing and new data analytics, supported by advanced simulations and domain expertise. The main purpose of this position is to develop machine learning systems using appropriate tools and algorithms to support the R&D and deployment at industrial grade of analytics applications. In this capacity, you will be able to work on our next generation data-driven solutions for the Mobility industry, within a lean startup environment, in collaboration with engineering & mobility experts, data engineers, DevOps/MLOps engineers, and HMI designers/storytellers.

 

Key accountabilities:

 

Develop, deploy, and maintain Machine Learning models and retraining systems:

  • Integrate data science models into Data and ML pipelines in collaboration with data scientists and data engineers
  • Design and execute machine learning tests and experiments, by applying best practices for experiment tracking and model registry
  • Build and orchestrate MLOps pipelines including CI/CD to automate data ingestion and transformation, model (re-)training, (re-)deployment, inference and monitoring
  • Support the industrialization of scalable data science solutions through automation and continuous delivery
  • Identifying changes in models and shifts in data distribution that could affect model performance, and apply appropriate measures for protecting against drifts
  • Apply strong testing and quality assurance practices
  • Support field trials with our customers using the mobility analytics software modules and tools
  • Analyses and checks the suitability of an algorithm if it caters the needs of the current task/business problem
  • Attend meetings, submit work progress reports and perform related duties as required.

 

 

Performance measurements:

 

  • Number of models deployed and kept compliant with requirements according to prescribed performance metrics
  • On Time Delivery (OTD)
  • Developments Quality Cost Delivery (QCD)

 

 

Educational Requirements

Mandatory:

  • Degree in computer science or engineering supplemented by extensive training in data science/ML or related discipline

Desirable:

  • Master’s degree in the fields of statistics or machine learning or applied mathematics or related disciplines

 

Experience

 

Mandatory:

  • Excellent knowledge of Python programming, with software engineering skills including DevOps and CI/CD pipelines
  • Experience with Python data science stack (pandas, scikit-learn, Keras, Numpy, TensorFlow)
  • Experience in building supervised and unsupervised ML models and in optimizing model (hyper-)parameters tuning for performance and costs
  • Strong mathematical skills (probability and statistics, algebra, optimization)
  • Knowledge of continuous integration tools and technologies (Jenkins, Ansible, Git)
  • Experience with SQL/NoSQL database management
  • Experience with LINUX environment (shell scripting)

     

 

Desirable:

  • Experience with cloud technologies, preferably on Azure
  • Experience with containerization and orchestration tools (Docker, Airflow, NiFi, Kubernetes, OpenFaaS) for production
  • Experience in MLOps frameworks (e.g.  MLFlow and DVC)
  • Experience in big data technologies (e.g. Spark, Hadoop, Apache Kafka etc.)
  • Proficiency with web APIs development and design (e.g. REST)
  • Experience in writing technical documentation
  • Agiles procedures

     

 

 

Competencies & Skills

  • Proven track record in development of high-quality ML solutions, including implementation of testing strategies and debugging
  • You are truly passionate about machine learning algorithms and technologies, ready to take new challenges, you are proactive and possess strong organizational and planning skills, along with excellent communication and presentation capabilities
  • Flexibility to work successfully with both local and remote / international teams
  • Fluent English

Perspective candidates will be asked to present their previous work (if possible) to demonstrate their ML proficiency levels

 

 

 

 

You don’t need to be a train enthusiast to thrive with us. We guarantee that when you step onto one of our trains with your friends or family, you’ll be proud. If you’re up for the challenge, we’d love to hear from you!

 

Important to note

As a global business, we’re an equal-opportunity employer that celebrates diversity across the 63  countries we operate in. We’re committed to creating an inclusive workplace for everyone.

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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

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Tags: Airflow Ansible APIs Azure Big Data CI/CD Computer Science Data Analytics DevOps Docker Engineering Git Hadoop Industrial Jenkins Kafka Keras Kubernetes Linux Machine Learning Mathematics MLFlow ML models MLOps NiFi NoSQL NumPy Pandas Pipelines Python R R&D Scikit-learn Shell scripting Spark SQL Statistics TensorFlow Testing

Perks/benefits: Career development Startup environment

Region: Europe
Country: France

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