Track This Job
Add this job to your tracking list to:
- Monitor application status and updates
- Change status (Applied, Interview, Offer, etc.)
- Add personal notes and comments
- Set reminders for follow-ups
- Track your entire application journey
Save This Job
Add this job to your saved collection to:
- Access easily from your saved jobs dashboard
- Review job details later without searching again
- Compare with other saved opportunities
- Keep a collection of interesting positions
- Receive notifications about saved jobs before they expire
AI-Powered Job Summary
Get a concise overview of key job requirements, responsibilities, and qualifications in seconds.
Pro Tip: Use this feature to quickly decide if a job matches your skills before reading the full description.
Workload: Full-time
Contract type: Contract of Mandate / B2B
Role Overview
We’re looking for a Machine Learning Systems Engineer to join a global leader in geospatial analytics.
In this role, you’ll be responsible for Machine Learning workflow orchestration platform – a mission-critical ecosystem that underpins the entire AI division. You’ll design, build, and maintain scalable infrastructure capable of supporting massive data and compute workloads.
Key Responsibilities
- Design and build large-scale distributed systems running on Kubernetes (up to 10,000 nodes).
- Ensure platform reliability, scalability, and high availability in production environments.
- Collaborate closely with AI, SRE, and Data Engineering teams to streamline model training and deployment pipelines.
- Define and drive best practices in CI/CD, observability, and cloud infrastructure management.
- Take ownership of incident response, on-call rotations, and reliability improvements.
Required Skills & Experience
- Kubernetes (K8s) – Deep, production-level expertise is non-negotiable.
- Able to design and deploy clusters from scratch, manage massive workloads (10,000+ nodes).
- Cloud Experience (AWS / GCP) – Strong hands-on experience managing infrastructure in cloud environments.
- SRE / DevOps Background – Solid understanding of reliability engineering, monitoring, on-call operations, and CI/CD.
- Programming Skills (Python preferred) – Strong coding ability; Go or Rust experts open to learning Python are also welcome.
- Experience with MLOps platforms and lifecycle management.
- Familiarity with workflow orchestration tools (e.g., Airflow, Kubeflow).
- Access to LinkedIn Learning
- B2B contract + benefits
Key Skills
Ranked by relevanceReady to apply?
Join eConsulting and take your career to the next level!
Application takes less than 5 minutes

