Senior MLOps Engineer

Technologies we use

About the project

Your responsibilities

• Designing and deploying K8s clusters on AWS
• Auto-scaling: from 10 to 1000 nodes depending on needs
• Resource optimization: CPU, GPU, memory management

Our requirements

• Proficiency in Python and Linux, with strong knowledge of designing scalable, distributed systems
• Hands-on experience in designing, implementing, and maintaining MLOps workflows, including CI/CD pipelines, monitoring, and production optimization
• Strong background in cloud computing (AWS/GCP), infrastructure as code (Terraform), containerization, and orchestration (Kubernetes)
• Solid understanding of modern software development practices such as test-driven development (TDD), systems thinking, and CI/CD automation
• Experience deploying and managing observability tools such as Prometheus, Grafana, and OpenTelemetry to ensure high reliability and performance in production ML systems
• Expertise in scaling and optimizing distributed systems for large-scale, multi-node computations
• 80% of the work is K8s

This is how we organize our work

This is how we work

Team members

This is how we work on a project

Development opportunities we offer

What we offer

• Work with cutting-edge technology - high-resolution aerial imagery and city-scale 3D content
• Exposure to AI and advanced AI datasets
• Experience with geospatial technology and integrated spatial tools
• Medical care
• Sport Card (MultiSport)
• MultiLife (mental and physical wellbeing)
• Attractive employee referral program
• Nearmap subscription (naturally)

Benefits