Machine Learning Engineer

Vantor Inc. is hiring a Machine Learning Engineer to transform raw satellite imagery into trusted, well-labeled data and to build, deploy, and operate machine learning models and production inference pipelines based on that data.

Responsibilities

• Build systems that convert raw satellite imagery into trusted, well-labeled data.
• Develop machine learning algorithms that use the labeled data to produce models.
• Design robust, scalable, low-latency solutions in collaboration with internal domain experts, external annotation partners, and Vantor’s Machine Learning and Software Engineering teams.
• Create pipelines for large geospatial imagery and metadata, including sensor, acquisition, and geolocation attributes, and ensure reliable data movement between annotation, storage, and model training systems.
• Track data lineage and versioning to trace every label back to its source image, guideline version, and annotator.
• Develop, adapt, deploy models that propose 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 prioritized for labeling next.
• Ship a reliable data service and connect it with training and deployment of computer vision models into a continuously improving system.

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.
• Hands-on 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, 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.

Technologies

• Python
• Deep learning models
• Managed compute
• Databases
• Storage
• Identity and access management
• Containerized services
• CI/CD pipelines
• Infrastructure-as-code
• Batch or real-time inference pipelines
• Cloud Run
• Cloud SQL
• Cloud Storage
• IAM
• Service account management
• Vertex AI
• Vertex AI Pipelines
• Model deployment
• Kubeflow Pipelines
• PostgreSQL
• PostGIS
• GeoTIFF
• GDAL
• Rasterio
• Shapely
• Fiona
• GeoPandas

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

Eligibility

To be eligible for this position, you must be a U.S. person as defined as a U.S. citizen, permanent resident, Asylee, or Refugee.

Export Control / ITAR

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).

Preferred Qualifications

• 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 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 tasks such as object detection, semantic or instance segmentation, or change detection, ideally applied to overhead imagery.

Pay Transparency

• Salary range: USD 128,000 - 215,600 per year
• Base pay within Colorado: $128,000.00 - $170,000.00 - $187,000.00 annually
• Base pay within New Jersey: $128,000.00 - $170,000.00 - $187,000.00 annually
• Base pay within Delaware: $128,000.00 - $170,000.00 - $187,000.00 annually
• Base pay within the Washington, DC metropolitan area: $140,000.00 - $187,000.00 - $205,700.00 annually
• Base pay within California: $147,000.00 - $196,000.00 - $215,600.00 annually
• For all other states, geographic cost of labor is used to develop market-driven ranges, so each location where Vantor hires may have a different range.
• Starting pay falls within the listed range and is based on factors such as experience, qualifications, skills, location, and market conditions.
• Candidates meeting minimum requirements should not expect compensation at the top of the range.

Application Window

• The application window is three days from the date the job is posted and remains open until a qualified candidate is identified.
• If reposted, it will remain posted for three days from the repost date and continue until a qualified candidate is identified.
• The job posting date is listed on Vantor’s Career page at the top of each job posting.

To Apply

Submit your application via Vantor’s Career page.