Time since we first saw it
Day 7
Similar jobs usually come down between day 6 and day 69.
From 4,284 similar postings that came down. Coming down is not always a hire.
Data Engineer
Reads like a ML Engineer role: putting models into production.
Liège, Belgium
Actively hiring, first seen by us 7 days ago- Pay
- Pay not listed
- Work setting
On-site — work setting source
Work setup in the employer’s posting: On-site
From the employer’s posting- Employment
Full-time — employment source
Employment type in the employer’s posting: Full-time
From the employer’s posting
What you’ll work on
Full postingPrepare industrial data from machines, sensors, MES and quality systems
Design, train, validate and deploy ML and Computer Vision models
Develop and maintain end-to-end MLOps pipelines
Deploy AI models in containerised, hybrid on-premise/cloud environments
Monitor model performance, data drift and reliability
From the employer’s posting
Explore, analyse and prepare industrial data from machines, sensors, MES and quality inspection systems.
Design, train, validate and deploy Machine Learning and/or Computer Vision models for industrial applications.
Develop and maintain end-to-end MLOps pipelines, including training, deployment, monitoring and model lifecycle management.
Deploy AI models in production using containerised architectures and AWS SageMaker, across hybrid on-premise/cloud environments.
Monitor model performance, data drift and reliability, ensuring continuous improvement.
What you’ll bring
All qualificationsCore experience
- Experience and competencies
- Experience in industrial manufacturing, MES, predictive maintenance or OT environments.
- Good communication skills
- Strong experience developing and deploying Machine Learning models (predictive analytics, anomaly detection, time series and/or Computer Vision).
- Knowledge of Data Lakes, real-time streaming, Snowflake or Dataiku.
- Proficiency in Python, Pandas, NumPy, Scikit-learn, PyTorch and/or TensorFlow.
Qualification wording
What are we looking for in you? Experience and competencies
Experience in industrial manufacturing, MES, predictive maintenance or OT environments.
Good communication skills
Strong experience developing and deploying Machine Learning models (predictive analytics, anomaly detection, time series and/or Computer Vision).
Knowledge of Data Lakes, real-time streaming, Snowflake or Dataiku.
Proficiency in Python, Pandas, NumPy, Scikit-learn, PyTorch and/or TensorFlow.
Posting record
Report an errorActively hiringFirst seen by us 7 days ago, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Oct 27, 20267 days ago
- Recorded sightings
- 23
- Last seen by us
- Nov 4, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Scalian is hiring
4 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Hiring is picking up
- Takes jobs down at a usual pace
- 50% of open jobs were reposted
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- AWS
- Docker
- Grafana
- Kafka
- Kubernetes
- S3
- SageMaker
- Snowflake
- NumPy
- pandas
- PyTorch
- scikit-learn
- TensorFlow
Where the posting names them
- Strong experience developing and deploying Machine Learning models (predictive analytics, anomaly detection, time series and/or Computer Vision). - Proficiency in Python, Pandas, NumPy, Scikit-learn, PyTorch and/or TensorFlow. - Solid knowledge of MLOps practices, including model/data versioning, automated pipelines, CI/CD and performance monitoring.
- Develop and maintain end-to-end MLOps pipelines, including training, deployment, monitoring and model lifecycle management. - Deploy AI models in production using containerised architectures and AWS SageMaker, across hybrid on-premise/cloud environments. - Monitor model performance, data drift and reliability, ensuring continuous improvement.
- Solid knowledge of MLOps practices, including model/data versioning, automated pipelines, CI/CD and performance monitoring. - Hands-on experience with AWS, particularly SageMaker, S3, IAM, ECR and CloudWatch. - Experience with containerisation (Docker/Podman) and orchestration (Kubernetes/OpenShift).
- Familiarity with Kafka, MQTT, Prometheus or Grafana. - AWS certifications in Machine Learning, Data Analytics or Cloud technologies. Soft skills:
- Hands-on experience with AWS, particularly SageMaker, S3, IAM, ECR and CloudWatch. - Experience with containerisation (Docker/Podman) and orchestration (Kubernetes/OpenShift). - Knowledge of Git, software testing and production model deployment (API, batch or streaming).
- Knowledge of Data Lakes, real-time streaming, Snowflake or Dataiku. - Familiarity with Kafka, MQTT, Prometheus or Grafana. - AWS certifications in Machine Learning, Data Analytics or Cloud technologies.
- Experience in industrial manufacturing, MES, predictive maintenance or OT environments. - Knowledge of Data Lakes, real-time streaming, Snowflake or Dataiku. - Familiarity with Kafka, MQTT, Prometheus or Grafana.
Your next step
Complete your application on jobs.smartrecruiters.com. The employer’s form will show what is required.
Applying through SmartRecruiters
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Already applied? Track this application
Has Scalian posted this job before?
Yes. We’ve followed one other Data Engineer job there since June 2026. It is still up.
About the role
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
US government figures for computer and information research scientists
- Median yearly pay, May 2025
- $140,300
- Expected change, 2025 to 2035
- 21.8% more jobsagainst 3.5% for all jobs
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Job description
Job Description
Are you a Data Engineer looking for a new challenge?
If you want to expand your reach and share your knowledge with a team of professionals, contribute to the development of your colleagues' or Clients' skills, want to consolidate your expertise and grow on innovative projects, this is your opportunity!
What this experience will bring you
First of all, an interesting technical challenge but also an overview of our Client's projects.
We will build your career together and accompany you towards the development of new skills and technical leadership.
What will your role be?
We are looking for a Data Engineer to perform the following activities:
- Explore, analyse and prepare industrial data from machines, sensors, MES and quality inspection systems.
- Design, train, validate and deploy Machine Learning and/or Computer Vision models for industrial applications.
- Develop and maintain end-to-end MLOps pipelines, including training, deployment, monitoring and model lifecycle management.
- Deploy AI models in production using containerised architectures and AWS SageMaker, across hybrid on-premise/cloud environments.
- Monitor model performance, data drift and reliability, ensuring continuous improvement.
- Collaborate with IT, Manufacturing, Quality and Maintenance teams to integrate AI solutions into existing systems and CI/CD pipelines.
- Document technical solutions and promote MLOps best practices across teams.
Qualifications
What are we looking for in you? Experience and competencies
- Engineering degree in Computer Science, Data Science, AI, Applied Mathematics or a related field.
- Minimum 5 years of experience as a Data Scientist or Machine Learning Engineer, preferably in industrial or production environments.
- Strong experience developing and deploying Machine Learning models (predictive analytics, anomaly detection, time series and/or Computer Vision).
- Proficiency in Python, Pandas, NumPy, Scikit-learn, PyTorch and/or TensorFlow.
- Solid knowledge of MLOps practices, including model/data versioning, automated pipelines, CI/CD and performance monitoring.
- Hands-on experience with AWS, particularly SageMaker, S3, IAM, ECR and CloudWatch.
- Experience with containerisation (Docker/Podman) and orchestration (Kubernetes/OpenShift).
- Knowledge of Git, software testing and production model deployment (API, batch or streaming).
Nice to Have
- Experience in industrial manufacturing, MES, predictive maintenance or OT environments.
- Knowledge of Data Lakes, real-time streaming, Snowflake or Dataiku.
- Familiarity with Kafka, MQTT, Prometheus or Grafana.
- AWS certifications in Machine Learning, Data Analytics or Cloud technologies.
Soft skills:
- Problem solving
- Good communication skills
- Goal-oriented approach
- Self-Driven
- Proactive to solution
- Teamwork
Languages:
- French (fluent, oral and written)
- English (fluent, oral and written)
Additional Information
Why would you take the plunge?
Because Scalian is a group of specialists, carrying an ambitious development project, focused on innovation and committed to its customers where you can:
- Build a tailor-made career path, varied and adapted to your desires, thanks to the variety of missions in your area of expertise and the bridges between trades
- Learn by the quality of the projects on which you will intervene, in your specialty, and thanks to the large training catalog delivered by our internal Academy
- Have an attractive social framework that respects everyone's needs (telework agreement, crèches, social coverage, flexibility, soft mobility, etc.)
- Contribute to R&D topics or participate in internal projects
- Be part of a friendly team that will make work rhyme with pleasure!
So want to expand the frame? Contact us to talk about it.
Company Description
Who are we?
Human and technology to scale sustainable performance
Founded in 1989, Scalian is a French group with an international dimension, with offices in Europe and North America, specializing in business transformation through its dual mastery of business processes and digital technologies.
In the TOP10 engineering consulting companies in France, the Group is involved in service activities in the management of industrial projects, supply chain (costs, quality, deadlines, performance), architecture and development of embedded digital systems, computer systems applications. Information and Artificial Intelligence.
Scalian also deploys solutions for optimizing projects or the performance of organizations and responds to the challenges of transformation for leaders in industry and the tertiary sector (energy, transport, space, banking, health, environment, etc.).
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
Liège, Belgium
- Develop and maintain end-to-end MLOps pipelines, including training, deployment, monitoring and model lifecycle management. - Deploy AI models in production using containerised architectures and AWS SageMaker, across hybrid on-premise/cloud environments. - Monitor model performance, data drift and reliability, ensuring continuous improvement.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.