Deep Learning Infrastructure Engineer - Autonomous Flight

Skydio; Finland; On-site; EUR 148,874 - 243,015; Full time

Benefits offered by this job

Stock options

Health insurance

Paid vacation

Job summary

Skydio in Finland seeks a Deep Learning Infrastructure Engineer to design and scale data pipelines, annotation workflows, and tools that support our DL and AI training efforts across the fleet of Skydio drones.

You will work with cloud platforms, containers, and ML Ops to optimize training workflows, ensure security and compliance, and push the boundaries of autonomous flight while collaborating across teams.

Qualifications

• Hands-on experience building large-scale, performant data processing pipelines.
• Experience with cloud-based ML platforms, ML Ops platforms and databases.
• Understanding of security and compliance requirements in ML infrastructure.
• Experience building and managing ML pipelines including data preparation, model training, deployment and monitoring.

Responsibilities

• Design and implement scalable, extensible, interactive data pipelines and annotation workflows.
• Build tools that leverage state-of-the-art machine learning systems for efficient data exploration and curation across the fleet of Skydio drones.
• Design and implement pipelines for data ingestion, versioning, model training, deployment and monitoring.
• Optimize and scale deep learning training workflows to improve team iteration velocity.
• Leverage best practices to uphold and improve Skydio’s engineering standards.

Skills

Data engineering

Cloud ML platforms

Containerization

ML Ops

Security & compliance

ML data pipelines

Software lifecycle

Tools

Docker

Kubernetes

Job description

Skydio in Finland seeks a Deep Learning Infrastructure Engineer to design and scale data pipelines, annotation workflows, and tools that support our DL and AI training efforts across the fleet of Skydio drones.

You will work with cloud platforms, containers, and ML Ops to optimize training workflows, ensure security and compliance, and push the boundaries of autonomous flight while collaborating across teams.