MLOps Engineer

Job not on LinkedIn

🔥 2 minutes ago

🇧🇷 Brazil – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 Machine Learning Engineer

👻 Ghost score 25%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Seekerh

WebsiteLinkedInAll Job Openings

1 - 10 employees

Founded 2019

💼 Consulting

🏥 Healthcare

📣 Marketing

Consulting • Healthcare • Marketing

Seekerh is a recruitment and selection consultancy that connects companies with the right professionals through strategic hiring, cultural-fit assessment and rapid, tech-enabled processes. The firm provides tailored recruitment, selection and on-demand talent projects, acting as a strategic partner to support sustainable organizational growth and improved hiring outcomes.

📋 Description

• Design, implement, and maintain automated pipelines for data products and Machine Learning models • Serve as a bridge between Data Engineering, Data Science, and Operations • Ensure governance, scalability, automation, and reliability across Azure analytics environments • Support the continuous evolution of data and AI solutions • Work with one of the consulting firm’s major clients

🎯 Requirements

• Strong experience with Azure Databricks and Apache Spark • Advanced knowledge of the Azure ecosystem, including Azure Data Factory, Azure Data Lake Storage Gen2, Azure Synapse Analytics, and Azure Key Vault • Experience with Git and version control strategies • Hands-on experience with Azure DevOps, including Azure Repos and Azure Pipelines • Knowledge of building CI/CD pipelines for data projects • Experience with monitoring using Azure Monitor, Log Analytics, or equivalent tools • Experience with MLflow for experiment tracking and model versioning • Knowledge of Azure Machine Learning for managing the model lifecycle • Experience deploying models for real-time inference (Real-Time Endpoints) and batch processing (Batch Endpoints) • Familiarity with Docker for application packaging • Knowledge of Azure Container Registry (ACR) • Experience with Azure Kubernetes Service (AKS) for deploying Machine Learning services • Preferred: experience with Terraform or Bicep for Infrastructure as Code (IaC) • Preferred: knowledge of Lakehouse architectures • Preferred: experience with Delta Lake • Preferred: knowledge of Unity Catalog • Preferred: knowledge of observability using Prometheus and Grafana • Preferred: experience with Generative AI, LLMOps, or applications based on generative models • Preferred: Microsoft Azure certifications (AZ-400, DP-203, DP-100, or AI-102)

🏖️ Benefits

• The engagement may be on a contractor basis (PJ, without benefits) or under a Brazilian employment contract (CLT)