Pay
$166K–$240K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 1,279 postings in the last year. Stated ranges, not salaries paid.
ML Infrastructure Engineer
South San Francisco, California, USA
Live, first seen by us 27 days ago- Pay
- Pay not listedSimilar roles state $166K–$240K
- Work setting
- Not stated
- Employment
- Not stated
What you’ll work on
Full postingBuild and operate infrastructure that lets learning algorithms use large fleet data
Design data and ML systems for dataset creation, validation, training, evaluation and deployment
Own and improve data pipelines that feed the ML development loop
Find and fix bottlenecks in orchestration, performance and reproducibility of ML development
From the employer’s posting
Build and operate software infrastructure that enables learning algorithms to leverage Zipline’s 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
About Zipline
Zipline is the world’s largest and most experienced drone delivery service.
In the employer’s words · Read in context
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Oct 8, 202627 days ago
- Recorded sightings
- 102
- Last seen by us
- Nov 4, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Time since we first saw it
Day 27
Similar jobs usually come down between day 6 and day 69.
From 4,381 similar postings that came down. Coming down is not always a hire.
Zipline is hiring
7 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Takes jobs down at a usual pace
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- AWS
- Kubernetes
- Terraform
- PyTorch
Where the posting names them
- 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 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
- 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.
- 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.
Your next step
Complete your application on www.zipline.com. The employer’s form will show what is required.
Applying through Greenhouse
- No account needed: the form is one page, with an “Autofill my application” option that reads your resume.
- Greenhouse doesn’t read resumes over 2.5 MB, or details placed in a header, footer, text box, table or second column. The file still attaches, but a recruiter has to type you in by hand.
Already applied? Track this application
About the role
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
US government figures for computer and information research scientists
- Median yearly pay, May 2025
- $140,300
- Expected change, 2025 to 2035
- 21.8% more jobsagainst 3.5% for all jobs
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Job description
About Zipline
Zipline is the world’s 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 world’s 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 world’s 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 we’ve 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 people’s 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.
About You and The Role
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.
What You'll Do
- Build and operate software infrastructure that enables learning algorithms to leverage Zipline’s 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.
What You'll Bring
- 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.
What Else You Need To Know
The starting cash ranges for this role is $160,000 - $250,000. 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 candidate's 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 candidate’s experience, skills, and demonstrated scope:
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!
Voluntary Self-Identification
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.
Source details
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- Pay
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- Location & working pattern
South San Francisco, California, USA
Working pattern and location restrictions need checking in the full posting.
- Work authorization
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