Machine Learning Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Create systems that convert raw satellite imagery into reliable, accurately labeled data.

• Design machine learning algorithms and models utilizing geospatial datasets.

• Construct pipelines for extensive geospatial imagery and metadata, encompassing sensor, acquisition, and geolocation attributes.

• Ensure reliable data transfer between annotation, storage, and model training systems.

• Monitor data lineage and versioning to ensure labels can be traced back to their source imagery, guideline versions, and annotators.

• Develop, modify, and implement models that produce suggested annotations.

• Build and manage production inference pipelines.

• Assess model performance against labeled datasets.

• Utilize model feedback to identify which imagery should be labeled next.

• Collaborate with internal subject matter experts, external annotation partners, and teams in Machine Learning and Software Engineering.

• Maintain production systems through debugging, observability, secure configuration, and incident response.

⛳️ Requirements

• Over 5 years of pertinent experience in machine learning engineering, data engineering, backend software engineering, or a closely related technical field.

• Practical experience in training, fine-tuning, or adapting deep learning models using a contemporary ML framework.

• Proven experience in deploying machine learning models to production, which includes building batch or real-time inference pipelines and managing model versions.

• Practical experience in building and operating services on a major cloud platform, covering managed compute, databases, storage, and identity and access management.

• Experience in constructing and managing workflow orchestration for data or ML pipelines.

• Familiarity with containerized services, CI/CD pipelines, and infrastructure-as-code.

• Demonstrated ability to support production systems, including debugging, observability, secure configuration, and incident response.

• Strong skills in Python application development.

• A Bachelor’s degree in Computer Science, Machine Learning, Data Engineering, Geospatial Science or GIS, Remote Sensing, or a related field, or equivalent demonstrated experience.

• Experience with Google Cloud Platform services such as Cloud Run, Cloud SQL, Cloud Storage, IAM, and service account management.

• Familiarity with Vertex AI, including Vertex AI Pipelines, training jobs, and model deployment, or similar tools like Kubeflow Pipelines.

• Experience with PostgreSQL and PostGIS, covering spatial data modeling and managing schema migrations in production.

• Experience working with satellite or aerial imagery, including raster formats like GeoTIFF, coordinate reference systems, and tools such as GDAL, Rasterio, Shapely, Fiona, and GeoPandas.

• Experience in developing computer vision models for object detection, semantic or instance segmentation, or change detection, preferably in relation to overhead imagery.

🏝️ Benefits

• Comprehensive 401(k) plan with company matching.

• Access to mental health resources.

• Assistance with student loan repayment.

• Reimbursement for adoption expenses.

• Pet insurance coverage.

• Incentives available based on contributions, company performance, and/or individual achievements.