Autonomy Engineer - ML & DL Infrastructure

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

Overview

Skydio is the leading US drone company and the world leader in autonomous flight. We leverage breakthrough AI to create the world’s most intelligent flying machines for use by our enterprise, public safety, defense and other customers. Learning a semantic and geometric understanding of the world from best-in-class visual data is the core of our autonomy system. We push the boundaries of what is possible with deep networks, AI and ML to accelerate progress in intelligent aerial robots that can autonomously navigate in unknown environments and deliver operational value to users.

If you are excited about leveraging massive amounts of structured video data to solve open problems in object detection and tracking, optical flow estimation and segmentation, we would love to hear from you.

As a Deep Learning Infrastructure Engineer, you will be responsible for building and scaling the infrastructure that supports Skydio’s DL and AI training efforts. You will work at the nexus of Skydio’s autonomy and cloud teams to deliver new capabilities and empower AI/ML solutions at Skydio.

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.

What Makes You a Good Fit

• Demonstrated hands-on experience with data engineering and building large-scale, performant and efficient data processing pipelines.
• Hands-on experience with cloud-based ML platforms, containerization technologies, 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.
• Ability to take a concept and systematically drive it through the software lifecycle: architecture, development, testing, deployment and monitoring.
• Ability to navigate and contribute within a complex codebase.
• Strong communication skills and the ability to collaborate effectively at all levels of technical depth.
• Obtaining FAA Part 107 certification within the first 60 days of employment is strongly encouraged for all Skydio employees and required for certain positions.

Compensation and Benefits

Compensation for regular, full-time employees includes a base salary, equity in the form of stock options, and comprehensive benefits. Salary will vary based on factors including skill level and experience. Relocation assistance may be provided for eligible roles. The annual base salary range for this position is $170,000 - 277,500. Skydio provides eligible employees with group health insurance and benefits including paid vacation, sick leave, holiday pay and a 401K plan. This position and all benefits are subject to applicable laws and company policies.

EEO and Hiring Statement

At Skydio we believe that diversity drives innovation. We are committed to growing a network of people, programs, and resources to nurture an inclusive culture. Qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or other characteristics protected by applicable laws. For positions located in the United States, Skydio may use E-Verify to confirm employment eligibility. To learn more about E-Verify, please visit https://www.e-verify.gov/

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