MLOps Engineer
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 1d ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 2d ago
The date the source published, not the day we noticed it (2026-11-04). Last seen at its source just now.
We have tracked this listing since 4 Nov 2026 (1 days). The employer's own board has carried it every time we have read it, most recently just now.
Is it remote?
Marked remote on the employer's board
Their board carries a remote setting on this posting — a field they filled in, not wording we read. The location field names somewhere specific, which is usually where the team or the entity sits.
Who may apply?
Serbia, Romania
The description states no restriction of its own. This is the source's own tag.
Pay not stated
Similar roles pay €81.7k–117.7k/yr
Middle 50% of 51 listings that do state pay — Engineering · all levels · Eastern Europe · EUR/year. This employer has published no salary; this is what comparable listings we hold disclose, never converted between currencies or periods. How this is calculated.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
-
Workable employer's own board first seen 1d ago · last seen just now
The listing
Join Sedona Digital, a fast-growing scale-up organization with an ambition to be recognized as one of the leading technology companies servicing high-tech, global enterprises across Technology, Finance, and Life Sciences sectors. Our global client base needs builders: engineers and developers who love technology, have deep expertise in software, engineering, and cloud technologies, and importantly, have a passion for culture and customers.
- We obsess about our customers
- We build outstanding technical solutions
- We create an awesome culture
- We accelerate learning and careers
We are looking for a skilled MLOps Engineer to join our team and play a key role in bridging the gap between our Data Science and Infrastructure teams. You will be responsible for supporting the Data Science team in MLOps-related tasks while also helping in DevOps initiatives, including CI/CD pipeline creation, provisioning of cloud resources using tools like Terraform, and Kubernetes orchestration. You will collaborate closely with data scientists and engineers to deploy data pipelines, train machine learning models, and manage their deployment within scalable cloud environments while ensuring high performance, security, and reliability throughout the ML lifecycle.
The main responsibilities of the position include:
- Assist in designing, implementing, and maintaining scalable MLOps pipelines on AWS using services such as SageMaker, EC2, EKS, S3, Lambda and other relevant AWS tools
- Coordinate with our platform team to troubleshoot Kubernetes clusters (EKS) to orchestrate the deployment of machine learning models and other microservices
- Develop and maintain CI/CD pipelines for model and application deployment, testing, and monitoring
- Collaborate closely with Data Science, and DevOps team to streamline the model development lifecycle, from experimentation to production deployment
- Implement security best practices, including network security, data encryption, and role-based access controls within the AWS infrastructure
- Monitor, troubleshoot, and optimize data and ML pipelines to ensure high availability and performance
- Set up and manage model monitoring systems for performance drift, ensuring continuous model improvement
Requirements
- Bachelor’s degree in Computer Science, Engineering, or related field
- 2+ years of hands-on experience in MLOps, DevOps, or related fields
- Knowledge and preferable working experience in AWS services for machine learning, such as SageMaker, EKS, S3, EC2, Lambda, and others
- Exposure to Kubernetes for container orchestration
- Experience with Docker Exposure to infrastructure-as-code tools such as Terraform or CloudFormation
- Familiarity with CI/CD tools such as GitLab CI
- Understanding machine learning model lifecycle
- Familiarity with monitoring and logging solutions like Prometheus, Grafana, CloudWatch and ELK Stack
- Understanding of networking concepts and cloud security best practices
- Proficiency in Python and Bash, and comfortable working in Linux environments
- Strong problem-solving and communication skills
The following will be considered an advantage:
- Experience working with serverless architectures and event-driven processing on AWS
- Familiarity with advanced Kubernetes concepts such as Helm
- Experience with Data Engineering pipelines, ETL processes, or big data platforms
- Experience with ML frameworks like TensorFlow, PyTorch and Keras
- Experience with ML platforms like Kubeflow and/or SageMaker
- Experience with workflow engines like Argo Workflows and/or Airflow
Benefits
- Work from home
- Medical insurance given after the probation period
- Training on market trends and client needs
- Continuous learning and personal development opportunities
- Holiday allowance in line with local legislation
- Competitive compensation package
- Performance-based bonus
- Fun budget for team events