Time since we first saw it
Day 83
Up longer than most. Similar jobs usually come down between day 6 and day 69.
From 4,339 similar postings that came down. Coming down is not always a hire.
(Senior) ML Ops Engineer
Lousado, Braga, Portugal
Live, first seen by us 83 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 postingDesign and manage CI/CD pipelines for ML models from development to production
Build and maintain scalable ML infrastructure on cloud platforms using infrastructure-as-code
Automate deployment, monitoring, and rollback processes for reliability and reproducibility
Implement monitoring and feedback loops for model performance and continuous improvement
Provide technical leadership and mentorship to the team
From the employer’s posting
Design and manage CI/CD pipelines for ML models from development to production
Build and maintain scalable ML infrastructure on cloud platforms using infrastructure-as-code
Automate deployment, monitoring, and rollback processes for reliability and reproducibility
Implement monitoring and feedback loops for model performance and continuous improvement
Provide technical leadership and mentorship, fostering knowledge sharing and best practices
What you’ll bring
All qualificationsCore experience
- Expertise in CI/CD and automation tools (e.g., GitHub Actions);
- Proficiency in containerization and orchestration (Docker, Kubernetes);
- Hands-on experience with ML model deployment and lifecycle management (MLflow, SageMaker);
- Good knowledge of cloud platforms (AWS or Azure) and infrastructure-as-code practices;
- Familiarity with monitoring and performance tracking tools (Grafana) and workflow orchestration (Airflow);
- Solid understanding of software engineering and DevOps practices (testing, GitOps, CI/CD design patterns);
Qualification wording
Expertise in CI/CD and automation tools (e.g., GitHub Actions);
Proficiency in containerization and orchestration (Docker, Kubernetes);
Hands-on experience with ML model deployment and lifecycle management (MLflow, SageMaker);
Good knowledge of cloud platforms (AWS or Azure) and infrastructure-as-code practices;
Familiarity with monitoring and performance tracking tools (Grafana) and workflow orchestration (Airflow);
Solid understanding of software engineering and DevOps practices (testing, GitOps, CI/CD design patterns);
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Aug 13, 202683 days ago
- Recorded sightings
- 618
- Last seen by us
- Nov 4, 2026
- Employer says posted
- Jul 28, 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
Continental is hiring
4 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Hiring has slowed
- Takes jobs down at a usual pace
- 25% 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
- SQL
- AWS
- Azure
- Docker
- Grafana
- Kubernetes
- MLflow
- SageMaker
- Airflow
Where the posting names them
- >3 years of professional experience as a MLOps Engineer; - Strong programming skills in Python and SQL; - Expertise in CI/CD and automation tools (e.g., GitHub Actions);
- Hands-on experience with ML model deployment and lifecycle management (MLflow, SageMaker); - Good knowledge of cloud platforms (AWS or Azure) and infrastructure-as-code practices; - Familiarity with monitoring and performance tracking tools (Grafana) and workflow orchestration (Airflow);
- Expertise in CI/CD and automation tools (e.g., GitHub Actions); - Proficiency in containerization and orchestration (Docker, Kubernetes); - Hands-on experience with ML model deployment and lifecycle management (MLflow, SageMaker);
- Good knowledge of cloud platforms (AWS or Azure) and infrastructure-as-code practices; - Familiarity with monitoring and performance tracking tools (Grafana) and workflow orchestration (Airflow); - Solid understanding of software engineering and DevOps practices (testing, GitOps, CI/CD design patterns);
- Proficiency in containerization and orchestration (Docker, Kubernetes); - Hands-on experience with ML model deployment and lifecycle management (MLflow, SageMaker); - Good knowledge of cloud platforms (AWS or Azure) and infrastructure-as-code practices;
Your next step
Complete your application on jobs.smartrecruiters.com. The employer’s form will show what is required.
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Has Continental posted this job before?
Yes. We’ve followed one other (Senior) ML Ops Engineer job there since June 2026. It came down after 0 days.
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
Join Continental’s Digital Solutions Department as a MLOps Engineer
In Digital Solutions, we drive innovation for connected mobility and deliver cutting-edge digital products to our global fleet customers. As a MLOps Engineer, you will be at the forefront of transforming machine learning into scalable, production-ready solutions.
You will design, deploy, and maintain robust ML pipelines, ensuring seamless integration of models into production environments and optimizing their performance at scale. Working closely with Data Scientists, Data Engineers, and cross-functional teams, you will enable AI-driven insights that power smarter, safer, and more efficient mobility worldwide.
Main responsibilities:
- Design and manage CI/CD pipelines for ML models from development to production;
- Build and maintain scalable ML infrastructure on cloud platforms using infrastructure-as-code;
- Automate deployment, monitoring, and rollback processes for reliability and reproducibility;
- Implement monitoring and feedback loops for model performance and continuous improvement;
- Collaborate with data scientists and engineers to integrate ML models and standardize workflows;
- Provide technical leadership and mentorship, fostering knowledge sharing and best practices.
Qualifications
- Academic degree in Computer Science, IT, Engineering, Mathematics, or related field;
- >3 years of professional experience as a MLOps Engineer;
- Strong programming skills in Python and SQL;
- Expertise in CI/CD and automation tools (e.g., GitHub Actions);
- Proficiency in containerization and orchestration (Docker, Kubernetes);
- Hands-on experience with ML model deployment and lifecycle management (MLflow, SageMaker);
- Good knowledge of cloud platforms (AWS or Azure) and infrastructure-as-code practices;
- Familiarity with monitoring and performance tracking tools (Grafana) and workflow orchestration (Airflow);
- Solid understanding of software engineering and DevOps practices (testing, GitOps, CI/CD design patterns);
- Experience with Agile project management methods (Scrum, Kanban);
- Experience working in an international team (desirable);
- Proficient English language skills (spoken / written).
Additional Information
Our offer:
- Integration in a challenging and international work environment;
- Flexible working model;
- Agile and collaborative working style;
- Continuous opportunities for personal development and learning.
We are committed to fostering a workplace where everyone feels safe, respected, and valued. All kind of applications are welcome.
Ready to drive with Continental? Take the first step and fill in the online application.
Company Description
Continental is a leading tire manufacturer and industry specialist. Founded in 1871, the company generated sales of €39.7 billion in 2024 and currently employs around 95,000 people in 54 countries and markets.
Tire solutions from the Tires group sector make mobility safer, smarter, and more sustainable. Its premium portfolio encompasses car, truck, bus, two-wheel, and specialty tires as well as smart solutions and services for fleets and tire retailers. Continental has been delivering top performance for more than 150 years and is one of the world’s largest tire manufacturers. In fiscal 2024, the Tires group sector generated sales of 13.9 billion euros. Continental's tire division employs more than 57,000 people worldwide and has 20 production and 16 development sites.
Source details
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- Location & working pattern
Lousado, Braga, Portugal
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