Machine Learning Engineer

🕒 October 8

🇺🇸 United States – Remote

💵 $128k - $215.6k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 Machine Learning Engineer

👻 Ghost score 0%

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Vantor

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

🎖️ Defense

📦 Logistics

💼 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

🏖️ 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