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<p>Machine Learning Engineer/ Data Architect</p><p><strong>Location:</strong> Oakland, CA (Hybrid)</p><p><strong>Contract:</strong> 12 months</p><p><br></p><p>About the Company</p><p>A large, California-based energy and utilities organization focused on leveraging advanced analytics and machine learning to support critical infrastructure and wildfire risk mitigation initiatives.</p><p><br></p><p>Role Overview</p><p>Seeking a <strong>Data Architect / Machine Learning Engineer</strong> to bridge research and production by designing and implementing scalable ML and data solutions. This role combines <strong>hands-on engineering</strong> with <strong>architecture and technical leadership</strong>, supporting wildfire consequence modeling efforts.</p><p><br></p><p>Key Responsibilities</p><ul><li>Design and implement <strong>scalable ML and data architectures</strong> in cloud environments (AWS)</li><li>Build and deploy <strong>production-grade ML pipelines and data systems</strong></li><li>Translate research models into <strong>maintainable, real-world applications</strong></li><li>Develop APIs and system integrations for ML solutions</li><li>Partner with researchers, product teams, and leadership to deliver solutions</li><li>Communicate technical concepts effectively to cross-functional stakeholders</li></ul><p><br></p><p>Must-Haves</p><ul><li>Experience developing and deploying <strong>machine learning systems in production</strong></li><li>Strong <strong>Python</strong> and <strong>PySpark</strong> skills</li><li>Background in <strong>data architecture and system design</strong></li><li>Experience with <strong>AWS</strong> (S3, SageMaker, Lambda, Glue)</li><li>Strong analytical, problem-solving, and communication skills</li></ul><p><br></p><p>Nice-to-Have</p><ul><li>Experience with <strong>Snowflake and/or Palantir Foundry</strong></li><li>Geospatial analytics tools (e.g., geopandas, rasterio, GDAL, rioxarray, dask)</li><li>Background in <strong>wildfire, environmental, or risk modeling</strong></li><li>Experience supporting <strong>research-to-production ML workflows</strong></li></ul><p><br></p><p>Ideal Candidate Profile</p><ul><li>Hybrid <strong>architect + hands-on engineer</strong></li><li>Experience building <strong>scalable, cloud-native ML platforms</strong></li><li>Strong ability to <strong>translate research into production systems</strong></li><li>Comfortable advising leadership and collaborating across technical and non-technical teams</li></ul>
