Senior MLOps/DevOps (EU remote)

Established in 1997 Softeq was built from the ground up to specialize in new product development and R&D tackling the most difficult problems in the tech sphere. Now weve expanded to offer early-stage innovation and ideation plus digital transformation business consulting. Our superpower is to deliver all of this under one roof on a global scale. So lets get started and build a better future together!

Locations/type of contract:

EU country (B2B contract directly with Softeq fully remote)

We are looking for an experienced and motivated engineer to join our Data Science team within Medication Delivery Solutions (MDS) Business as the MLOps Engineer. As an MLOps Engineer you will play a crucial role in the deployment monitoring and maintenance of machine learning models. You will work closely with data scientists software engineers and IT operations to ensure that our machine learning models are reliable scalable and performing optimally in production environments. Your expertise will be essential in automating and streamlining our ML workflows enhancing model reproducibility and ensuring continuous integration and delivery. The MLOps Engineer will directly report to the Director of Data Science.

Responsibilities:

Design build and maintain the infrastructure required for efficient development deployment and monitoring of machine learning models.

Implement CI/CD pipelines for machine learning applications.

Develop and manage cloud-based and on-premises solutions for model training deployment and monitoring.

Ensure the scalability reliability and performance of machine learning systems.

Collaborate with data scientists to understand and implement requirements for model serving versioning and reproducibility.

Monitor and optimize model performance in production identifying and resolving issues proactively.

Automate repetitive tasks to improve efficiency and reduce the risk of human error.

Maintain documentation and provide training to team members on MLOps best practices.

Stay updated with the latest developments in MLOps tools technologies and methodologies.

Communicate and share knowledge with other team members and actively participate in various learning-sharing opportunities

Requirements:

Bachelors or Masters degree in Computer Science Engineering or a related field.

3 years of experience in MLOps DevOps or related fields.

Strong programming skills in Python with experience in other languages such as Java C or Scala being a plus.

Experience with ML frameworks such as TensorFlow PyTorch and/or scikit-learn.

Proficiency with CI/CD tools such as Jenkins or GitLab CI.

Hands-on experience with cloud platforms such as AWS Google Cloud or Azure.

Familiarity with containerization and orchestration tools like Docker and Kubernetes.

Knowledge of infrastructure-as-code tools such as Terraform or CloudFormation.

Strong understanding of machine learning lifecycle including data preprocessing model training evaluation and deployment.

Excellent problem-solving skills and the ability to work independently as well as part of a team.

Strong communication skills and the ability to explain complex technical concepts to non- technical stakeholders.

Very good English language skills both written and verbal (min. B2)

Preferred Qualifications:

Experience with feature stores model registries and monitoring tools such as MLflow Tecton or Seldon.

Familiarity with data engineering tools like Apache Spark Kafka or Airflow.

Knowledge of security best practices for machine learning systems.

Experience with A/B testing and model performance monitoring