MLOps Engineer

🔥 20 hours ago

🇲🇽 Mexico – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 Machine Learning Engineer

👻 Ghost score 11%

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.

Apply Now

Find Similar Remote Jobs

Set Up Email Alert For New Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

Atos

WebsiteLinkedInAll Job Openings

10,000+ employees

💼 Consulting

🏥 Healthcare

📦 Logistics

Consulting • Healthcare • Logistics

Atos is a global leader in digital transformation, providing a wide range of solutions and services across industries. The company specializes in cloud and infrastructure services, digital business platforms, technology consulting, and cybersecurity, with a focus on enhancing user experiences and supporting enterprise digital journeys. Atos is committed to sustainability and innovation, partnering with various organizations to drive digital advancements, such as its role as the official IT partner for the UEFA and the Olympic Games.

📋 Description

• Apply MLOps practices and manage the machine learning lifecycle • Process data and automate ML workflows using Python • Query and manage databases using SQL • Use Google Cloud Platform (GCP) for MLOps and machine learning workflows • Orchestrate workflows using Cloud Composer and Apache Airflow • Schedule and manage data and ML pipelines • Transform data and support analytics engineering with Dataform • Automate and monitor pipelines • Support CI/CD pipelines and ML model deployment • Use containerization technologies such as Docker and Kubernetes

🎯 Requirements

• Strong experience in MLOps practices and machine learning lifecycle management • Proficiency in Python for data processing, automation, and ML workflows • Strong knowledge of SQL and database querying • Hands-on experience with Google Cloud Platform (GCP) • Experience with Cloud Composer (Apache Airflow on GCP) for workflow orchestration • Expertise in Apache Airflow for scheduling and managing data and ML pipelines • Experience with Dataform for data transformation and analytics engineering • Understanding of workflow orchestration, pipeline automation, and monitoring • Experience with CI/CD pipelines and ML model deployment (preferred) • Knowledge of containerization technologies such as Docker and Kubernetes (preferred) • Fluent English

🏖️ Benefits

• Diversity and inclusion commitment • Fair work environment • ESG and CSR commitment