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Machine Learning Engineer

đŸ”„ 1 minute ago

đŸ‡ș🇾 United States – Remote

đŸ’” $128k - $215.6k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

đŸ€– Machine Learning Engineer

đŸ‘» Ghost score 0%

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Vantor

1001 - 5000 employees

đŸŽ–ïž Defense

📩 Logistics

đŸ’Œ Consulting

Defense ‱ Logistics ‱ Consulting

Vantor is a spatial intelligence company that builds an AI-ready "living globe" and a commercial imaging satellite constellation to unify sensor data across space, air, and ground. It provides software platforms and products for real-time tasking, sensor orchestration, high-resolution basemaps, radar and optical imagery, and autonomous ISR capabilities used by defense, intelligence, government, and commercial customers.

📋 Description

‱ Build systems that turn raw satellite imagery into trusted, well-labeled data ‱ Develop machine learning algorithms and models from geospatial datasets ‱ Build pipelines for large geospatial imagery and metadata, including sensor, acquisition, and geolocation attributes ‱ Move data reliably between annotation, storage, and model training systems ‱ Track data lineage and versioning so labels can be traced to source imagery, guideline versions, and annotators ‱ Develop, adapt, and deploy models that generate proposed annotations ‱ Build and operate production inference pipelines ‱ Evaluate model performance against labeled data ‱ Use model feedback to determine which imagery should be labeled next ‱ Collaborate with internal domain experts, external annotation partners, and Machine Learning and Software Engineering teams ‱ Support production systems through debugging, observability, secure configuration, and incident response

🎯 Requirements

‱ 5+ years of relevant experience in machine learning engineering, data engineering, backend software engineering, or a closely related technical role ‱ Hands-on experience training, fine-tuning, or adapting deep learning models using a modern ML framework ‱ Experience deploying machine learning models into production, including building batch or real-time inference pipelines and managing model versions ‱ Hands-on experience building and operating services on a major cloud platform, including managed compute, databases, storage, and identity and access management ‱ Experience building and operating workflow orchestration for data or ML pipelines ‱ Experience owning containerized services, CI/CD pipelines, and infrastructure-as-code ‱ Proven ability to support production systems, including debugging, observability, secure configuration, and incident response ‱ Strong Python application development skills ‱ Bachelor's degree in Computer Science, Machine Learning, Data Engineering, Geospatial Science or GIS, Remote Sensing, or a related discipline, or equivalent demonstrated experience ‱ Experience with Google Cloud Platform services, including Cloud Run, Cloud SQL, Cloud Storage, IAM, and service account management ‱ Experience with Vertex AI, including Vertex AI Pipelines, training jobs, and model deployment, or with similar tools such as Kubeflow Pipelines ‱ Experience with PostgreSQL and PostGIS, including spatial data modeling and managing schema migrations in production ‱ Experience working with satellite or aerial imagery, including raster formats such as GeoTIFF, coordinate reference systems, and tools such as GDAL, Rasterio, Shapely, Fiona, and GeoPandas ‱ Experience developing computer vision models for object detection, semantic or instance segmentation, or change detection, ideally applied to overhead imagery

đŸ–ïž Benefits

‱ Robust 401(k) with company match ‱ Mental health resources ‱ Student loan repayment assistance ‱ Adoption reimbursement ‱ Pet insurance ‱ Incentive eligible with a target based on contribution, company performance, and/or individual results achieved

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