Senior Machine Learning Engineer
To see similar active jobs please follow this link: Remote Development jobs
Location: This role is remote. However, given the cross-functional communication responsibilities, it is preferred that you be within 3 hours of Pacific time.
About Pachama:
Pachama harnesses AI and satellite data to empower companies to confidently invest in nature. Using the latest technological advances, Pachama delivers continuous insight into how forests sequester carbon, protect wildlife and benefit local communities. These insights enable leading companies to find the world’s best projects and track their impact over time while also helping land stewards earn an income protecting nature with tools to develop carbon projects and secure funds.
Experience & Skills We’re Looking For:
You've built scalable and fault-tolerant distributed systems that process large amounts of data
You've worked with ML models in production systems
Experience working in cluster environments and an understanding of the related distributed systems concepts (CPU/GPU interactions/transfers, latency/throughput bottlenecks, pipelining/multiprocessing, etc)
Experience with algorithms and data structures, domain-driven design, and software engineering fundamentals. Some examples of tools in our tech stack include Kubernetes, Dask, Flyte. Open source geospatial tools that are also part of our tech stack include Rasterio, Geopandas, and Xarray
Experience working with terrestrial ecosystem geospatial data such as land cover, ecosystem classifications, and biophysical data
You're comfortable with fast-paced execution and rapid iteration startup environment
You're excited by product impact
Interdisciplinary collaboration and deep user empathy
What You Will Help Us With:
Contribute to our geospatial data warehouse and platform for scientists and machine learning engineers
Construct robust pipelines for the ingest of geospatial data
Implement cutting edge pre-processing algorithms for sensor data to produce quality features for ML
Contribute to tools and infrastructure to increase iteration time and improve developer experience
Contribute to infrastructure to accelerate research and experimentation
Develop plans for cross-team initiatives related to infrastructure and deliver on them
You'll Have The Opportunity To:
Approach problems with curiosity and humility
Own solutions end-to-end
Take part in strategic thinking
Leave code better than when you found it
Communicate well and document better
Have fun!!
$106,155 - $168,500 a year
The salary range for this position is $106,155 USD to $168,500 USD. Salary ranges are determined by role, level, and location. The salary for each posting reflects the compensation for new hire salaries for the position across all geographic locations. Individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. The position is also eligible for equity.
Even if you don’t meet all these requirements, we encourage you to apply if this job description excites you. We are looking for ambitious people to help make an impact on climate change. That purpose requires us to bring together a diverse set of people with different backgrounds, perspectives, and skills to create solutions that work for all.
About the job
Senior Machine Learning Engineer
To see similar active jobs please follow this link: Remote Development jobs
Location: This role is remote. However, given the cross-functional communication responsibilities, it is preferred that you be within 3 hours of Pacific time.
About Pachama:
Pachama harnesses AI and satellite data to empower companies to confidently invest in nature. Using the latest technological advances, Pachama delivers continuous insight into how forests sequester carbon, protect wildlife and benefit local communities. These insights enable leading companies to find the world’s best projects and track their impact over time while also helping land stewards earn an income protecting nature with tools to develop carbon projects and secure funds.
Experience & Skills We’re Looking For:
You've built scalable and fault-tolerant distributed systems that process large amounts of data
You've worked with ML models in production systems
Experience working in cluster environments and an understanding of the related distributed systems concepts (CPU/GPU interactions/transfers, latency/throughput bottlenecks, pipelining/multiprocessing, etc)
Experience with algorithms and data structures, domain-driven design, and software engineering fundamentals. Some examples of tools in our tech stack include Kubernetes, Dask, Flyte. Open source geospatial tools that are also part of our tech stack include Rasterio, Geopandas, and Xarray
Experience working with terrestrial ecosystem geospatial data such as land cover, ecosystem classifications, and biophysical data
You're comfortable with fast-paced execution and rapid iteration startup environment
You're excited by product impact
Interdisciplinary collaboration and deep user empathy
What You Will Help Us With:
Contribute to our geospatial data warehouse and platform for scientists and machine learning engineers
Construct robust pipelines for the ingest of geospatial data
Implement cutting edge pre-processing algorithms for sensor data to produce quality features for ML
Contribute to tools and infrastructure to increase iteration time and improve developer experience
Contribute to infrastructure to accelerate research and experimentation
Develop plans for cross-team initiatives related to infrastructure and deliver on them
You'll Have The Opportunity To:
Approach problems with curiosity and humility
Own solutions end-to-end
Take part in strategic thinking
Leave code better than when you found it
Communicate well and document better
Have fun!!
$106,155 - $168,500 a year
The salary range for this position is $106,155 USD to $168,500 USD. Salary ranges are determined by role, level, and location. The salary for each posting reflects the compensation for new hire salaries for the position across all geographic locations. Individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. The position is also eligible for equity.
Even if you don’t meet all these requirements, we encourage you to apply if this job description excites you. We are looking for ambitious people to help make an impact on climate change. That purpose requires us to bring together a diverse set of people with different backgrounds, perspectives, and skills to create solutions that work for all.