About the Role:

Planet is looking for a Senior Machine Learning Engineer with a proven background in delivering machine learning products at scale.

This role will be in the Applied Machine Learning engineering team which delivers novel machine learning powered products for both external customers and internal use. The team designs the algorithms, integrates these into production systems and maintains them via ML operations (MLOps).  For example, the team has developed Road and Building monitoring products based upon our satellite imagery, including global weekly mapping and change detection. They have also built the inference systems that generate cloud masks of all images produced by Planet. The core algorithms that have been developed typically use a combination of computer vision (DL & non-DL) and time series, all cemented in statistical and physical principles. Additionally, the team takes ML models from external partners and integrates them into our systems so that their output can be offered to Planet’s customers.

In this role, you will join a team of engineers working together on algorithm development and integration into our distributed compute platform. You will perform exploratory analysis on remote sensing data and build models and inference pipelines on top of our infrastructure. You will also design ML operations to maintain the performance of deployed models and pipelines. 

The team has a highly collaborative culture and is distributed remotely across USA and Canada.

Impact You’ll Own:

• Development of computer vision and time series algorithms
• Design of datasets to fit or evaluate algorithms
• Implementation of algorithms as scalable production code in Python
• ML operations to maintain production algorithms (monitoring, training, benchmarking, deploying, etc)

What You Bring:

• Solid understanding of fundamentals in remote sensing, statistics and machine learning
• Methodical and scientific thinking. Ability to plan and prioritize in time-constrained projects
• Experience building and maintaining ML models in production 
• Experience with distributed and scientific computing
• Experience with geospatial python libraries (e.g. GDAL, rasterio, shapely, etc)
• Experience with scientific python libraries (e.g. numpy, scipy, TensorFlow, etc)
• Fluency in Python in a Linux environment
• Experience with Git and Docker
• Excellent interpersonal skills, both verbal and written, with the ability to explain complex technical issues accurately to technical and non-technical audiences

What Makes You Stand Out:

• Experience building products using sensor or geospatial data
• Experience in remote sensing or related fields

Benefits While Working at Planet:

• Comprehensive Health Plan
• Wellness program and onsite massages in specific offices
• Flexible Time Off
• Recognition Programs
• Commuter Benefits
• Learning and Tuition Reimbursement
• Parental Leave
• Offsites and Happy Hours
• Volunteering Benefits

#LI-REMOTE