Machine Learning Engineer

Vantor Inc. is hiring a Machine Learning Engineer (onsite) to transform raw satellite imagery into trustworthy labels and production-ready computer vision models.

• Build systems that convert raw satellite imagery into trusted, well-labeled data
• Develop machine learning algorithms that use labeled data to produce models
• Partner with internal domain experts, external annotation partners, and Vantor’s Machine Learning and Software Engineering teams to design robust, scalable, low-latency solutions
• Create pipelines for large geospatial imagery and metadata, including sensor, acquisition, and geolocation attributes, and move data reliably between annotation, storage, and model training systems
• Track data lineage and versioning so each label can be traced back to its source image, guideline version, and annotator
• Develop, adapt, and deploy models that generate proposed annotations to reduce manual labeling effort and improve labeling decisions
• Build and operate production inference pipelines
• Evaluate model performance against labeled data
• Use model feedback to determine which imagery should be labeled next
• Ship a reliable data service, train and deploy a computer vision model, and connect both into a single continuously improving system

• 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 with a modern ML framework
• Experience deploying machine learning models in 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 (managed compute, databases, storage, 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

• Python
• Deep learning models
• Managed compute, databases, storage
• Identity and access management (IAM), service account management
• Containerized services, CI/CD pipelines
• Infrastructure‑as‑code
• Batch or real‑time inference pipelines
• Cloud Run, Cloud SQL, Cloud Storage
• Vertex AI, Vertex AI Pipelines
• Model deployment, Kubeflow Pipelines
• PostgreSQL, PostGIS
• GeoTIFF, GDAL, Rasterio, Shapely, Fiona, Geo Pandas

• 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

• To be eligible, you must be a U.S. person
  : U.S. citizen, permanent resident, Asylee, or Refugee
• Certain roles may be subject to U.S. export control laws
  , requiring U.S. person status as defined by 8 U.S.C. 1324b(a)(3)

• 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 similar tools such as Kubeflow Pipelines
• Experience with PostgreSQL and PostGIS, including spatial data modeling and schema migrations in production
• Experience working with satellite or aerial imagery and raster formats such as GeoTIFF, coordinate reference systems, and tools including GDAL,…