Rhizome is seeking a Software Engineer who can develop and scale Rhizome’s end-to-end Machine Learning pipelines and expose them through a common interface on a scalable Platform. The ideal candidate will have a strong background in developing ETL pipelines to ingest GBs to TBs of spatial data, extract features, perform statistical analyses, and deploy models in a Production Environment. Successful candidates will have practical experience working with GIS data, Relational Databases, and cloud environments like AWS or GCP. This role will initially report to the CTO.About RhizomeRhizome is at the forefront of developing decision intelligence technology at the intersection of climate science and infrastructure systems. Our team pursues this endeavor with the wisdom and steadiness of industry veterans, and the curiosity, grit, and energy of startup and technology enthusiasts. Our climate resilience SaaS platform helps utilities, governments, and industries plan for greater resilience to climate change and extreme weather by applying AI to a vast amount of information that characterizes infrastructure assets and their vulnerability to extreme weather. Focused on the $500B resilience investment gap on the grid today, our mandate is simple: Help electric utilities proactively adapt to climate change by integrating cutting-edge climate-asset intelligence into their existing planning workflows. As the world experiences record-breaking climate-related impacts, especially related to grid failures, our platform identifies future extreme weather vulnerabilities on utility assets at high resolutions and empowers planners to optimize investment deployments that keep society safe during natural hazard events.Roles and Responsibilities<ul><li>Design, construct, and maintain production-grade ML pipelines to combine and analyze large volumes of geospatial, climate + weather, and electric utility data on Rhizome’s Platform (ASPEN)</li><li>Design, construct, and maintain cloud-native training services in support of R&amp;D efforts using traditional ML, deep learning, and causal ML models</li><li>Work with cross-functional team to standardize, refine, and further develop analytic and ML workflows on Rhizome’s Platform, in support of customer deliverables</li><li>Contribute to ML model development at scale in context of reliability and resiliency for the electric grid</li><li>Develop deep familiarity with electric utility datasets and take ownership of integration of new datasets into our existing environments</li><li>Standardize and scale multi-tenant data storage and collaborate with Application Development team to deliver results through gridADAPT and gridFIRM</li><li>Develop and optimize versioned, scalable, repeatable and reliable pipelines for utility data that is in GIS and Tabular format to Delta Lake format</li><li>Scale, Automate and Maintain pipelines for statistical and ML use cases to serve&nbsp;internal and external customers </li></ul>Qualifications <ul><li>Exceptional Python programming skills with NumPy, SciPy, Xarrays</li><li>Experience with ML frameworks like scikit-learn, XGBoost, PyTorch, Keras, TensorFlow</li><li>Experience with model registration, deployment, and monitoring frameworks like MLFlow or Kubeflow</li><li>Exceptional programming skills with frameworks like Dagster or Airflow or Prefect</li><li>Exceptional programming skills with Databricks or Apache Spark or Amazon EMR or Cloudera</li><li>Deep expertise in storage optimization and partitioning on RDS, Postgres, PostGIS, Delta Lake</li><li>Hands on experience with GIS dataset and QGIS or ESRI</li><li>Hands on experience with multi-dimensional Climate or Weather data</li><li>Familiarity or hands on experience with Secure Cloud Development</li><li>Exceptional ability to diagnose data issues and discrepancies</li><li>Ability to modularize different stages of data ingestion and verification</li><li>Ability to write algorithms for data sanity checks and classification of different data elements</li><li>Ability to develop heuristics and suggestions for missing data items</li><li>Ability to validate and test pipelines and write functional test to validate the pipelines</li></ul>We’ll pay extra close attention if you have:<ul><li>Exposure or experience with Utility Tech Stack</li><li>Experience with GeoSpatial AI</li><li>Experience with cloud based analytics platforms like Vertex AI or Databricks</li><li>Exposure to applied ML and Data Engineering with Utility background</li></ul>Culture and Core ValuesAt Rhizome, we lead with compassion and empathy, aiming to understand before we help. Our thesis as technologists is that, in order to fulfill our mission to protect society from the impacts of climate change through intentional, intelligent infrastructure planning, we need to embark on a journey of respectfully listening, learning, and then problem-solving. This sentiment is represented through our core values:&nbsp; <ul><li>Empathy: Understanding and relating to problems, customers, and each other, with humility.</li><li>Creativity: Exploring with curiosity and building with intention.</li><li>Aspiration: Striving for societal impact, personal fulfillment, and simply doing good work.</li><li>Tenacity: Pushing past barriers and the status quo with a sense of optimism and determination.</li><li>Service Excellence: Delivering high-quality outcomes for our customers, colleagues, and communities.</li></ul>Compensation and BenefitsRhizome offers competitive salaries and an excellent package of benefits and stock options. Compensation is based on a variety of factors including experience, role, and location.

Rhizome is an AI-powered platform that helps electric utilities identify vulnerabilities from climate threats, quantify risk at high resolutions, and measure the economic and social benefits of grid-enhancing investments.

Software Engineer – ML & Platform

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Rhizome

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