MLOps Engineer

Our requirements

• 5+ years of hands-on experience in MLOps or ML Engineering
• Bachelor’s degree or higher in Computer Science or a related field
• Fluent in spoken and written English (minimum B2 level; mandatory)
• Proven experience in MLOps and deploying machine learning models on Kubernetes (e.g., MLflow, KServe, Ray, Ollama, vLLM)
• Knowledge of how to build, operate, and maintain container images
• 5+ years of hands-on experience in MLOps or ML Engineering
• Bachelor’s degree or higher in Computer Science or a related field
• Fluent in spoken and written English (minimum B2 level; mandatory)
• Proven experience in MLOps and deploying machine learning models on Kubernetes (e.g., MLflow, KServe, Ray, Ollama, vLLM)
• Knowledge of how to build, operate, and maintain container images
• Strong understanding of cloud-native platform architecture and distributed systems design
• Experience with relational and non-relational databases
• Proficiency with monitoring and observability tools (Prometheus, Grafana, Loki, ELK stack, or similar)
• Familiarity with Agile methodologies (Scrum, Kanban) and DevOps/MLOps practices
• Ability to design and implement data-driven applications using one of the following programming languages: Python, C++, Java, R, JavaScript, or C#

Optional

• Experience with jupytelab or general jupyter deployments (e.g. JupyterHub, Kubeflow Notebooks
• Familiarity with data engineering tools (Databricks, Clickhouse, DuckDB)
• Familiarity with event/message streaming platforms (Kafka, rabbitmq)
• Experience with cost optimization and security best practices in cloud environments
• Experience with additional tools for data processing (spark, pandas, OpenCV) and visualization (tensorboard, matplotlib)
• Background in building end-to-end ML infrastructure pipelines integrating CI/CD, monitoring, and performance tuning
• German language skills will be considered a strong advantage

Your responsibilities

• Deploying and maintaining machine learning models on Kubernetes clusters
• Design, build, and maintain scalable infrastructure for training, testing, deploying, and monitoring ML models
• Supporting a small team of data scientists and machine learning engineers in the maintenance and development of their infrastructure
• Making suggestions on how to build new (or improve upon existing) data infrastructure solutions
• Investigating and fixing arising problems on system, deployment, or application levels
• Automate ML pipelines (data preprocessing, training, validation, and deployment)
• Implement CI/CD, infrastructure as code, and best DevOps practices in ML environments
• Ensure observability and reliability of deployed models (logging, metrics, tracing, alerts, performance monitoring)
• Optimize resource usage and cloud costs
• Support continuous improvement and introduce new tools and standards for the ML platform.

This is how we organize our work

We are excited to meet passionate technology enthusiasts ready to drive meaningful change.

What we offer

• Fully remote work or the possibility to work from our Warsaw office
• Choice of cooperation model: employment contract (UoP) or B2B contract
• Flexible working hours
• Private medical care (Lux Med or PZU Zdrowie)
• MyBenefit or Pyszne.pl
• Self-development opportunities
• Internal and external training
• Certification opportunities
• English/German language lessons with native speakers
• International teams and projects
• Choice of working environment (Mac/Linux/Windows)
• The availability and terms of selected benefits may vary depending on the chosen form of cooperation.

Benefits

• sharing the costs of sports activities
• private medical care
• sharing the costs of foreign language classes
• sharing the costs of professional training & courses
• remote work opportunities
• flexible working time

QualityMinds Sp. z o.o.