MLOps Engineer role
SkillHuset Sweden ABSammanfattning
This role involves developing and deploying microservices-based solutions for machine learning algorithms, focusing on both batch and real-time processing. The position requires collaboration with Data Scientists to enhance ML models and ensure their performance in production environments. Candidates will work with cloud platforms like GCP and Azure, utilizing tools such as Kubeflow and Docker. This is a hands-on position ideal for those with extensive experience in MLOps and a strong backgroundJobbet i korthet
Anställningstyp
tillsvidareanstallning
Arbetstid
heltid
Ansök senast: 2026-08-29
Publicerad: 2026-07-30
Beskrivning
Responsibilities:
* Develop and deploy end-to-end microservices-based solutions for batch and real-time algorithms, including monitoring, logging, automated testing, and performance testing.
* Design, implement, and optimize MLOps pipelines using tools such as Kubeflow, Seldon, MLFlow, Docker, and Kubernetes.
* Collaborate with Data Scientists to enhance the ML model development process and ensure performance improvements.
* Ensure scalability, maintainability, and robustness of deployed machine learning models.
* Monitor and troubleshoot ML model performance and infrastructure issues in production (experience with Prometheus and Grafana is valuable).
* Support and enhance ML software infrastructure, including CI/CD, data storage, cloud services, security, and system monitoring.
* Work with cloud platforms, particularly GCP and Azure, to optimize resource allocation and costs.
* Stay up to date with the latest trends and best practices in MLOps.
Qualifications:
* Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
* 5+ years of experience as a Machine Learning Engineer or in a similar role.
* Proficiency in Python and experience with ML frameworks like TensorFlow, PyTorch, and scikit-learn.
* Strong understanding of MLOps best practices and tools, including Kubeflow, Seldon, MLFlow, Docker, and Kubernetes.
* Experience working with cloud platforms, especially GCP.
* Knowledge of data processing, ETL, and feature engineering techniques.
* Strong problem-solving skills and ability to work in a fast-paced, collaborative environment.
* Excellent communication and interpersonal skills.
* Develop and deploy end-to-end microservices-based solutions for batch and real-time algorithms, including monitoring, logging, automated testing, and performance testing.
* Design, implement, and optimize MLOps pipelines using tools such as Kubeflow, Seldon, MLFlow, Docker, and Kubernetes.
* Collaborate with Data Scientists to enhance the ML model development process and ensure performance improvements.
* Ensure scalability, maintainability, and robustness of deployed machine learning models.
* Monitor and troubleshoot ML model performance and infrastructure issues in production (experience with Prometheus and Grafana is valuable).
* Support and enhance ML software infrastructure, including CI/CD, data storage, cloud services, security, and system monitoring.
* Work with cloud platforms, particularly GCP and Azure, to optimize resource allocation and costs.
* Stay up to date with the latest trends and best practices in MLOps.
Qualifications:
* Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
* 5+ years of experience as a Machine Learning Engineer or in a similar role.
* Proficiency in Python and experience with ML frameworks like TensorFlow, PyTorch, and scikit-learn.
* Strong understanding of MLOps best practices and tools, including Kubeflow, Seldon, MLFlow, Docker, and Kubernetes.
* Experience working with cloud platforms, especially GCP.
* Knowledge of data processing, ETL, and feature engineering techniques.
* Strong problem-solving skills and ability to work in a fast-paced, collaborative environment.
* Excellent communication and interpersonal skills.
Ansök till tjänsten
MLOps Engineer role
OM FÖRETAGET
SkillHuset Sweden AB
