Machine Learning Engineer
Indexed description
Your future role
Alstom announces an opening for a Machine Learning Engineer. This position supports Alstom Data Science programs by developing, testing, validating, and industrializing data-driven solutions in the mobility domain. The primary goal of these programs is to develop AI/ML software modules to improve customer performance and experience using existing and new data analytics, supported by advanced simulations and domain experts. The main purpose of this position is to develop machine learning systems using appropriate algorithms and tools 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.
We’ll look to you for:
- 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 monitor
- 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
- Degree in computer science or engineering supplemented by extensive training in data science/ML or related disciplines
- 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)
- 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
- Enjoy stability, challenges and a long-term career free from boring daily routines
- Work with new security standards for rail signalling
- Collaborate with transverse teams and helpful colleagues
- Contribute to innovative projects
- Utilise our flexible working environment
- Steer your career in whatever direction you choose across functions and countries
- Benefit from our investment in your development, through award-winning learning
- Progress towards leadership and advanced technical roles
- Benefit from a fair and dynamic reward package that recognises your performance and potential, plus comprehensive and competitive social coverage (life, medical, pension)
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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