Data & Machine Learning Engineer
Technology, Data & Digital · Data, AI & Analytics · Data Engineering · Machine Learning · Data Science
In short
Vi söker en Data & Machine Learning Engineer till vår organisation för tidig varning ombord (AEW) för att forma framtiden för datadriven utveckling, testning, verifiering och utvärdering för GlobalEye-systemet. Du kommer att bygga och förbättra datapipelines, analyskapacitet och maskininlärningslösningar och samarbeta med olika ingenjörsteam för att omvandla teknisk data till handlingskraftiga insikter och skalbara lösningar.
Responsibilities
- Design, develop, and maintain scalable data pipelines for engineering and product data.
- Develop and improve machine learning workflows and supporting infrastructure.
- Analyze complex datasets and create solutions that generate measurable value for engineering and development teams.
- Collaborate with systems engineers, software developers, product owners, and domain experts across the organization.
- Help establish and mature data-driven ways of working.
- Identify opportunities where analytics, automation, and machine learning can improve engineering processes, product quality, and decision-making.
- Contribute to initiatives from concept through implementation and operational use.
- Support colleagues and stakeholders in understanding and adopting data, analytics, and machine learning methodologies.
Requirements
- Master's degree in Computer Science, Engineering Physics, Electrical Engineering, Data Science, Applied Mathematics, or a related engineering discipline.
- Experience in software development, data engineering, analytics, machine learning, or a similar technical field.
- Experience developing solutions using Python and modern data processing or machine learning frameworks.
- Understanding of data pipelines, data modeling, and modern data processing concepts.
- Ability to communicate and collaborate effectively with stakeholders across technical and executive business domains.
Desired Qualifications
- Experience with sensor data, sensor fusion, or real-time data processing.
- Experience working with complex technical products or systems in highly engineered environments.
- Knowledge of MLOps practices, model deployment, and workflow automation.
- Experience with cloud-based Data & AI platforms
- Experience with technologies such as Delta Lake, Iceberg, Kafka, Spark, Airflow, Dagster, MLflow, PyTorch, Pandas, JAX or other large-scale data & machine learning tools.
- Military service and/or defence-related experience.
Benefits
- Work at the intersection of Data Engineering, Analytics, and Machine Learning.
- Establish and grow data and machine learning capabilities.
- Develop technical solutions, explore new ways of working, and support the adoption of modern data-driven methods.
- Work with one of the world's most advanced Airborne Early Warning & Control (AEW&C) systems, GlobalEye.
- Contribute to initiatives from concept through implementation and operational use.
- Support colleagues and stakeholders in understanding and adopting data, analytics, and machine learning methodologies.
Skills
PythonDelta LakeIcebergKafkaSparkAirflowDagsterMLflowPyTorchPandasJAX
#Data Engineering#Analytics#Machine Learning#Python#Cloud#AEW&C Systems#GlobalEye
About Saab
As a leading defence and security company, we offer solutions that range from the depths of the oceans to high in the sky, on land and in cyberspace, to keep people and society safe. Empowered by our 22,000 talented people, we constantly push the boundaries of technology to create a safer, more sustainable and more equitable world. We design, manufacture and maintain advanced systems in aeronautics, weapons, command and control, sensors and underwater systems. We are headquartered in Sweden and have major operations all over the world and are part of the domestic defence capability of several…
Company
SaabJob Posted
1 day ago
Expires
in 2 weeks
Employment Type
Full Time
Work mode
On Site
Experience Level
Mid-Senior
Locations
Göteborg, Sweden
Qualification
Master
Applicants
Be an early applicant
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