ML Infrastructure Engineer

Zipline is the worlds largest and most experienced drone delivery service. We are on a mission to serve all humans equally by ensuring access to food medicine and essential goods anytime anywhere. We design build and operate the worlds largest autonomous logistics system delivering critical supplies quickly and reliably. Today Zipline operates on four continents makes a delivery somewhere in the world every 30 seconds and has completed millions of deliveries to date including blood vaccines medical supplies food and retail products.

Our customers include the worlds largest and most prominent healthcare systems governments retailers restaurants and global businesses who rely on us to save lives reduce emissions increase economic opportunity and provide delivery from point A to point B as fast as possible. The drone is only 15% of what weve built to enable seamless reliable global operations.

Our system strengthens supply chains reduces congestion and gives people time back. With more than 140 million commercial autonomous miles safely flown Zipline is redefining access to healthcare consumer products and food across the globe.

We operate at a global scale and are looking for practical problem solvers who thrive on real-world challenges and rapid growth. Our team is motivated by building systems that have a direct meaningful impact on peoples lives and by scaling the future of logistics. We are seeking people who sculpt from first principles enjoy facing adversity and can do the impossible at record breaking speeds.

As an ML Training & Inference Infrastructure Engineer on the Data Platform team you will be building and scaling the systems powering our data flywheel. This person will work at the intersection of autonomy and the infrastructure owning systems that make ML development faster reproducible observable and safe.

This role is for a strong software engineer who enjoys the full ML development cycle: data ingestion processing pipelines dataset management distributed training continuous model integration evaluation and deployment. The ideal candidate has strong production engineering habits and is excited to build infrastructure that helps real autonomous systems improve over time.

• Build and operate software infrastructure that enables learning algorithms to leverage Ziplines large-scale (quickly growing!) fleet data.
• Design scalable maintainable data and ML infrastructure for autonomy teams including dataset creation validation training evaluation and deployment.
• Own and improve data pipelines that feed into the ML development loop.
• Identify and mitigate bottlenecks in the ML development cycle especially around orchestration performance and reproducibility to increase the rate at which we can improve and scale the delivery experience.

• 3 years of professional software engineering experience ideally including ML infrastructure data infrastructure robotics autonomy aerospace medical devices or another safety-critical hardware/product environment.
• Strong software engineering practices in Python in a production setting; comfort designing APIs services schemas jobs and operational workflows.
• Experience building reproducible data pipelines and machine-learning pipelines.
• Experience monitoring data statistics system performance metrics pipeline failures and model/evaluation signals.
• Working knowledge of ML concepts such as datasets training evaluation optimization statistics and modern deep learning workflows.
• Generalist mindset and willingness to work across cloud services data platforms developer tooling and embedded/robotics-adjacent constraints.
• Experience with PyTorch or similar ML frameworks.
• Strong ownership clear communication and interest in building secure systems for mission-critical workflows.
• Experience with Kubernetes or other container orchestration systems for production workloads.
• Experience with cloud and on-premise production infrastructure preferably AWS and infrastructure-as-code tools such as Terraform or CloudFormation.

BONUS POINTS

• Experience deploying or evaluating ML systems on real robots autonomous vehicles drones or other hardware products.
• Experience with large-scale training systems feature stores data/versioned artifact stores model registries or experiment tracking.
• Experience with annotation systems dataset inspection tooling or active-learning workflows.

The starting cash ranges for this role is $160000 - $250000. Please note that this is a target starting cash range for a candidate who meets the minimum qualifications for this role. The final cash pay for this role will depend on a variety of factors including a specific candidates experience qualifications skills working location and projected impact. The total compensation package for this role may also include: equity compensation; discretionary annual or performance bonuses; sales incentives; benefits such as medical dental and vision insurance; paid time off; and more. This position may be hired at one of three levels based on the candidates experience skills and demonstrated scope:

• ML Infrastructure Engineer II: $160000 - $190000
• Senior ML Infrastructure Engineer: $190000 - $220000
• Staff ML Infrastructure Engineer: $220000 - $250000

Zipline is an equal opportunity employer and prohibits discrimination and harassment of any type without regard to race color religion age sex national origin disability status genetics protected veteran status sexual orientation gender identity or expression or any other characteristic protected by federal state or local laws or our own sensibilities.

We value diversity at Zipline and welcome applications from those who are traditionally underrepresented in tech. If you like the sound of this position but are not sure if you are the perfect fit please apply!

For government reporting purposes we ask candidates to respond to the below self-identification survey. Completion of the form is entirely voluntary. Whatever your decision it will not be considered in the hiring process or thereafter. Any information that you do provide will be recorded and maintained in a confidential file.

As set forth in Zipline s Equal Employment Opportunity policy we do not discriminate on the basis of any protected group status under any applicable law.