MLOps Engineer

Technologies we use

This is how we organize our work

This is how we work

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.

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

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

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