Data Infrastructure & MLOps Engineer (all genders)

Location: Berlin, Germany; hybrid. Applicants must be based in Germany and have the right to work in Germany. Visa sponsorship and relocation support are not available.

Company

hirify.global is a B2B SaaS platform used by millions of professionals to coordinate meetings and collaboration.

What you will do

• Design, build, and operate scalable infrastructure for data ingestion, transformation, storage, serving, analytics, and machine learning.
• Develop reliable batch and streaming pipelines and improve data discoverability, lineage, ownership, quality, and governance.
• Build MLOps workflows for experimentation, versioning, training, evaluation, deployment, rollback, retraining, and model serving.
• Manage secure cloud environments using infrastructure as code, automated deployments, capacity planning, and cost controls.
• Define reliability practices including service-level objectives, monitoring, alerts, dashboards, runbooks, on-call processes, and incident response.
• Partner with product, engineering, analytics, data science, security, and operations teams while creating reusable tooling and documentation.

Requirements

• Professional experience in data engineering, platform engineering, MLOps, DevOps, or a related role.
• Strong Python and SQL skills, including production-quality software and data pipeline development.
• Hands-on experience with cloud infrastructure, containers, CI/CD, and infrastructure as code.
• Experience with data warehouses, data lakes, workflow orchestration, and batch or streaming processing.
• Practical knowledge of machine learning lifecycle management, deployment, monitoring, reproducibility, and production reliability.
• Based in Germany with the right to work in Germany; visa sponsorship and relocation support are unavailable.

Nice to have

• Experience with Kubernetes, Terraform, Airflow, dbt, Spark, Kafka, MLflow, or similar tools.
• Experience operating machine learning systems in a B2B SaaS or high-growth technology environment.
• Knowledge of feature stores, vector databases, LLM applications, retrieval-augmented generation, or agentic AI systems.
• Experience with data quality, lineage, governance, privacy controls, ISO 27001, SOC 2, or GDPR programmes.

Culture & Benefits

• A team of more than 100 people distributed across four countries.
• Offices in Zurich, Berlin, and Belgrade, with additional remote colleagues in the USA.
• Environment based on mutual trust, respect, diversity, inclusion, and equal employment opportunity.
• Encouragement to contribute ideas, experiment, and implement agreed decisions quickly.

Hiring process

• Initial application review and BRYQ assessment.
• Hiring manager interview, technical assessment, and cross-functional technical interview.
• Executive interview and HR interview.