9 дней назад
MLOps Engineer (Azure/Databricks)
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): Building and operating production ML platforms on Azure Databricks, covering feature pipelines, model deployment, monitoring, governance, and retraining with an accent on reliability, scalability, security, and observability. Focus on designing ML lifecycle standards, diagnosing Databricks bottlenecks, implementing CI/CD and serving patterns, and supporting RAG and LLM applications.
Location: Hybrid in Barcelona, Spain or Munich, Germany
Company
combines strategy, frontier AI, technical integration expertise, and product development to deploy AI-native systems for regulated industries.
What you will do
- Design and operate ML platforms on Azure Databricks, including feature pipelines, MLflow tracking, model registries, training pipelines, and batch or online serving.
- Define model lifecycle standards for versioning, reproducibility, evaluation, promotion, deployment, rollback, and retraining.
- Build production deployment patterns, APIs, and CI/CD pipelines for models and data.
- Monitor data and concept drift, model quality, latency, reliability, and cost, with alerting and retraining triggers.
- Design scalable Databricks workloads, identify performance bottlenecks, and produce solution designs and delivery proposals.
- Establish ML governance, reusable platform templates, security controls, lineage, audit trails, and compliance-ready operating processes.
Requirements
- 5+ years of experience in MLOps, ML platform engineering, or a similar role, including production ML systems.
- Proven experience deploying, monitoring, troubleshooting, and managing the lifecycle of production models.
- Deep hands-on expertise with Azure, Azure Databricks, MLflow, and Unity Catalog; Azure ML experience is advantageous.
- Software-engineering skills covering packaging, testing, APIs, automation, containers, and CI/CD for models and data.
- Experience with Terraform, Infrastructure as Code, cloud networking, IAM, encryption, secrets management, governance, and observability.
- Working knowledge of Azure OpenAI or Azure AI Foundry, RAG, vector search, evaluation, and guardrails, plus strong stakeholder communication and mentoring skills.
Culture & Benefits
- Flexible working culture with a focus on work-life balance.
- Yearly education budget.
- Yearly sport budget.
- International, knowledgeable, and collaborative team.
- Opportunity to contribute to high-impact AI deployments and company growth.
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