Senior Software Engineer at Planet

Haarlem, North Holland, Netherlands

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Aerospace, Geospatial, Environmental, Agriculture, ForestryIndustries

Requirements

Expertise in designing, developing, and deploying machine learning solutions at scale
Experience at the intersection of machine learning (ML), software engineering, and remote sensing
Ability to work with satellite imagery for applications in agriculture, forestry, climate, land management, etc
Proficiency in building robust, scalable machine learning workflows and integrating them into distributed systems
Skills in designing and enhancing machine learning infrastructure for training, evaluation, and inference on global-scale datasets
Experience in backend and API design, with occasional front-end and DevOps tasks
Ability to collaborate with distributed teams of scientists, engineers, and clients across Europe and North America
Capability to establish and maintain machine learning operations (ML Ops) workflows for monitoring and optimizing deployed models
Willingness to work in a full-time, hybrid role requiring 3 days per week in Ljubljana or Haarlem office

Responsibilities

Design, develop, and deploy robust, scalable machine learning workflows and integrate them into distributed systems for real-world applications
Build tools to analyze remote sensing data from diverse sources to extract actionable insights
Design and improve ML infrastructure for training, evaluation, and inference on global-scale datasets, ensuring high performance and reliability
Build connections to internal systems, ensuring stable, secure, and reliable interfaces
Contribute to high- and low-level end-to-end system development, including backend and API design, with occasional front-end and DevOps tasks for geospatial applications
Collaborate closely with distributed teams of scientists, engineers, and clients, incorporating feedback to refine and enhance products
Establish and maintain machine learning operations workflows to monitor and optimize the performance of deployed models
Work on projects like mapping crop activities, detecting land changes, measuring forest carbon stocks, roads, buildings, and other Earth Observation topics

Skills

Machine Learning

Software Engineering

Remote Sensing

Satellite Imagery

ML Deployment

Python

Computer Vision

Data Processing

Cloud Platforms

Earth Observation

Planet

High-resolution satellite imagery subscription service

About Planet

Planet captures high-resolution satellite images of the Earth using a fleet of small satellites called Doves. These satellites provide near-daily, detailed imagery across eight different bands, allowing clients to monitor environmental changes, manage resources, plan urban developments, and respond to disasters. The company operates on a subscription-based model, giving clients access to a vast library of images and data analytics tools. This approach ensures consistent revenue as clients require ongoing updates. Planet differentiates itself by offering customized solutions and educational resources through Planet School, helping users effectively utilize their platform. The goal of Planet is to be a leader in the geospatial intelligence market, providing valuable insights through frequent and detailed Earth observation.

San Francisco, CaliforniaHeadquarters

2010Year Founded

$617.1MTotal Funding

IPOCompany Stage

Data & Analytics, AerospaceIndustries

1,001-5,000Employees

Benefits

Health Insurance

Dental Insurance

Vision Insurance

Health Savings Account/Flexible Spending Account

Unlimited Paid Time Off

Paid Vacation

Paid Sick Leave

Paid Holidays

Sabbatical Leave

Remote Work Options

Wellness Program

Mental Health Support

Home Office Stipend

Phone/Internet Stipend

Tuition Reimbursement

Equity

Commuter Benefits

Volunteering Paid Time Off

Parental Leave

Risks

Increased competition from companies like Antaris threatens market share.

Recent layoffs may impact operational efficiency and innovation.

Expansion of partnerships may stretch resources, reducing service quality.

Differentiation

Planet operates the largest fleet of Earth-imaging satellites globally.

Their subscription model ensures continuous revenue from diverse sectors.

Planet's AI-driven analytics enhance satellite imagery insights significantly.

Upsides

AI-driven analytics can expand into agriculture and urban planning sectors.

Partnerships with platforms like UP42 enhance data offerings and capabilities.

Smart city management using satellite data offers new revenue streams.

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