Machine Learning Engineer, Senior

Capgemini
2 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior

Job location

Tech stack

Agile Methodologies
Big Data
Continuous Integration
Data Validation
Data Visualization
Distributed Systems
Python
Machine Learning
Mainframes
Data Streaming
Systems Integration
Management of Software Versions
Virtualization Technology
Working Model 2D
Data Ingestion
Containerization
AI Platforms
Integration Tests
Data Analytics
Machine Learning Operations
Stream Processing
Data Pipelines

Job description

Job Type: Permanent / Full-Time Working Hours: 36-40 hours per week Working Model: Hybrid (50% on-site, 50% remote) Machine Learning Engineers promote the adoption of best standards in industrial code development across the ML&AI community. They do so by developing ML pipelines that are production-ready by design or by integrating existing ML solutions into industrial pipelines. They participate in the development, deployment and monitoring of AI services, which means they contribute to data quality checks, data flow design, the design of the models themselves and their overall integration into the production environment. ML Engineers are meant to facilitate the communication between AI & Analytics teams and IT production with regards to the deployment of ML models, ensuring that models put in production are equipped with the appropriate data pipelines and monitoring. As a Machine Learning Engineer, you will: Collaborate with Data Scientists to design and develop ML solutions with

Requirements

production constraints in mind. Select appropriate infrastructure, serving models, and data ingestion approaches to meet business requirements such as real-time processing and high data volumes. Unit, regression, and integration testing Support Data Scientists in using existing industrial AI platforms and CI/CD tools for building and monitoring AI services. Work closely with IT Production teams to configure and optimize target production environments. Ensure proper data quality checks, data flow design, and model integration within production systems. Minimum 4 years of relevant experience as an ML Engineer or related role Strong experience in Python (advanced level) Experience with containerization and virtualization technologies Code, model, and data versioning Solid understanding of Agile methodologies Experience with system integration across distributed systems, mainframe, and infrastructure components Knowledge of model compression techniques Exposure to Big Data technologies (e.g., Knowledge of data flow / stream processing Familiarity with data visualization tools You will join Capgemini Financial Services Benelux , working alongside passionate and skilled colleagues toward shared goals. Opportunities to work at the international forefront of technology It starts on day one. Working for Capgemini also means working in the international heart of innovation. The premier league of technology.

About the company

Capgemini ist einer der weltweit führenden Anbieter von Management- und IT-Beratung, Technologie-Services und Digitaler Transformation. Als ein Wegbereiter für Innovation unterstützt das Unternehmen seine Kunden bei deren komplexen Herausforderungen rund um Cloud, Digital und Plattformen.

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