обновлено 6 дней назад
MLOps Engineer
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
MLOps Engineer (Azure/Databricks): Orchestrating and maintaining machine learning pipelines from data ingestion through deployment and monitoring, with an accent on PySpark, Databricks, MLflow, CI/CD, and observability. Focus on automating reliable ML operations, detecting data and model issues, managing SLA/SLO ownership, and handling incidents across pipeline and serving infrastructure.
Location: Amsterdam, The Netherlands; hybrid work with two office days per week
Company
develops navigation software, mapping products, and technologies that help people, car manufacturers, enterprises, and developers understand and navigate the world.
What you will do
- Orchestrate and maintain ML pipelines covering ingestion, feature engineering, training, evaluation, deployment, monitoring, and repeatable operation on Azure and Databricks.
- Standardize experimentation with MLflow or similar tools, including tracking, artifacts, model registries, and deployment stages.
- Automate Databricks jobs and CI/CD workflows using GitHub Actions or Azure DevOps.
- Implement data and model observability for freshness, completeness, drift, training-serving skew, and SLA/SLO monitoring.
- Maintain security and compliance, and handle incidents and post-mortems for ML pipelines and serving infrastructure.
Requirements
- 3+ years of experience in data engineering or MLOps roles.
- Excellent Python software engineering skills, including test development.
- Fundamental understanding of machine learning and strong PySpark experience.
- Hands-on experience with Databricks and Delta Lake.
- Experience with Git, pull-request workflows, automated tests, environment pinning, and CI/CD for data or ML systems.
- Azure fundamentals, monitoring and dashboard development, clear communication, and an operational-excellence mindset with SLA/SLO ownership.
Nice to have
- Experience with Unity Catalog or Databricks Feature Store.
- Terraform experience for workspaces, clusters, jobs, and Unity Catalog objects.
- Telemetry domain exposure.
- Experience optimizing PySpark jobs and cloud costs through partitioning, caching, autoscaling, and spot capacity.
Culture & Benefits
- Hybrid work combining office collaboration with home working; additional options are available to work from the home country and abroad for a set number of days each year.
- Personal development budget, paid learning days, and access to O’Reilly and LinkedIn Learning.
- Enhanced parental leave, paid care leave, volunteering leave, and a competitive holiday plan with an additional birthday day off.
- Home-office setup budget and monthly home-office allowance.
- Inclusive international environment with more than 80 nationalities, plus annual Hackathon and DevDays events.
Hiring process
- Application screening followed by assessments and interviews.
- Successful candidates proceed through onboarding.
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