Job Description We are seeking a Machine Learning Engineerleaning Data Scientist to join the Wildfire Consequence Modeling team. This role is ideal for someone who can work effectively with academically oriented researchers while bringing a solution architecture and software engineering mindset to model design, implementation, and production grade systems. The team is composed primarily of individuals with academic backgrounds. This role will help balance the group by emphasizing practical problem solving, system design, and scalable machine learning solutions, while still engaging deeply in data science and model development. \\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\ Key Responsibilities Design, develop, and deploy machine learning systems supporting wildfire consequence modeling Collaborate closely with academic researchers and data scientists to translate research concepts into production ready models Lead or contribute to solution architecture for data and ML workflows, balancing performance, scalability, and maintainability Design and implement end to end ML pipelines, including data ingestion, feature engineering, model training, and inference Apply strong software engineering principles to machine learning model development Support and guide architectural decisions related to cloud infrastructure, tooling, and integrations Work hands on with geospatial data and analytics relevant to wildfire modeling Partner with the broader data science team to improve model robustness, scalability, and operational readiness We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce : Skills and Requirements Required Qualifications Professional experience developing and designing machine learning technologies and systems Strong Python skills, with experience building production grade data and ML solutions Experience with PySpark for large scale data processing Experience working on a data science or machine learning team, collaborating with researchers or academics Ability to both problem solve analytically and design scalable models and systems Comfortable operating as a hybrid Machine Learning Engineer / Data Scientist \\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\ Technical & Platform Experience Cloud & Data Platforms: oAWS ecosystem, including SageMaker, S3, Lambda, Glue oAnd/or experience with Snowflake oAnd/or Palantir Foundry Architecture & Systems: oSolution architecture for data and ML systems oModel pipelines, APIs, and system integrations \\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\ Geospatial & Domain Expertise Strong geospatial analytics experience using Python, including tools such as: orioxarray oGDAL orasterio ogeopandas odask SQL experience supporting geospatial or analytical workloads Experience or strong interest in wildfire spread or consequence modeling \\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\ Nice to Have / Preferred Experience in wildfire modeling, environmental modeling, or risk/consequence modeling Background working in applied ML environments where research transitions into production Experience mentoring or supporting academic researchers in applied engineering contexts \\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\ What Makes This Role Unique Opportunity to balance an academically driven team with practical, solution oriented engineering High impact work supporting wildfire risk and consequence analysis Strong influence over system design and technical direction Blend of data science depth and software engineering rigor

The role requires professional experience in developing and designing machine learning technologies and systems. Strong Python skills are necessary, along with experience in building production-grade data and ML solutions. Experience with PySpark for large-scale data processing is also required. Candidates should have experience working on a data science or machine learning team, collaborating with researchers or academics. The ability to analytically problem-solve and design scalable models and systems is essential. The position involves operating as a hybrid Machine Learning Engineer and Data Scientist.