Job description

Vantor is forging the new frontier of spatial intelligence, helping decision makers and operators navigate what’s happening now and shape what’s coming next. Vantor is a place for problem solvers, changemakers, and go-getters—where people are working together to help our customers see the world differently, and in doing so, be seen differently. Come be part of a mission, not just a job, where you can: Shape your own future, build the next big thing, and change the world. To be eligible for this position, you must be a U.S. Person, 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). Please review the job details below. Role Overview Vantor is seeking a Machine Learning Engineer to build the systems that turn raw satellite imagery into trusted, well-labeled data, and to develop machine learning algorithms to turn that data into models. Your work sets the quality, speed, and traceability of the datasets behind Vantor s geospatial and machine learning products. You will work closely with internal domain experts, external annotation partners, and Vantor s Machine Learning and Software Engineering teams to design robust, scalable, low-latency solutions. On the platform side, you will build pipelines for large geospatial imagery and metadata, including sensor, acquisition, and geolocation attributes, and move data reliably between annotation, storage, and model training systems. You will also track data lineage and versioning so every label can be traced back to its source image, guideline version, and annotator. On the machine learning side, you will develop, adapt, and deploy models that generate proposed annotations, cutting manual labeling effort and turnaround time. You will build and operate production inference pipelines, evaluate model performance against labeled data, and use model feedback to decide which imagery should be labeled next. This is a hands-on role for an engineer who is as comfortable shipping a reliable data service as training and deploying a computer vision model, and who can connect the two into a single, continuously improving system. Minimum 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. 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 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 tasks such as object detection, semantic or instance segmentation, or change detection, ideally applied to overhead imagery. Pay Transparency: To support pay transparency, Vantor includes salary ranges in all U.S. job postings. Starting pay for this role will fall within the listed range and will be based on factors such as experience, qualifications, skills, location, and market conditions. Candidates who meet the minimum requirements for the role should not expect to receive compensation at the top of the range. The listed range reflects the expected pay for this position, and final offers will be determined based on each candidate’s experience, expertise, and alignment with the role. ● The base pay for this position within Colorado is: $128,000.00 - $170,000.00 - $187,000.00 annually. ● The base pay for this position within New Jersey is: $128,000.00 - $170,000.00 - $187,000.00 annually. ● The base pay for this position within Delaware is: $128,000.00 - $170,000.00 - $187,000.00 annually. ● The base pay for this position within the Washington, DC metropolitan area is: $140,000.00 - $187,000.00 - $205,700.00 annually. ● The base pay for this position within California is: $147,000.00 - $196,000.00 - $215,600.00 annually. For all other states, we use geographic cost of labor as an input to develop market-driven ranges for our roles, and as such, each location where we hire may have a different range. Benefits: Vantor offers a competitive total rewards package that goes beyond the standard, including a robust 401(k) with company match, mental health resources, and unique perks like student loan repayment assistance, adoption reimbursement and pet insurance to support all aspects of your life. You can find more information on our benefits at: vantor.com Additionally, this position is incentive eligible with a target based on contribution, company performance, and/or individual results achieved; the specific incentive plan and target amount will be determined based on the role and breadth of contributions. The application window is three days from the date the job is posted and will remain posted until a qualified candidate has been identified for hire. If the job is reposted regardless of reason, it will remain posted three days from the date the job is reposted and will remain reposted until a qualified candidate has been identified for hire. The date of posting can be found on Vantor s Career page at the top of each job posting. To apply, submit your application via Vantor s Career page. EEO Policy: Vantor is an equal opportunity employer committed to an inclusive workplace. We believe in fostering an environment where all team members feel respected, valued, and encouraged to share their ideas. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, gender identity, sexual orientation, disability, protected veteran status, age, or any other characteristic protected by law.

Requirements

Must-haves

Please review the job details below.
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.

Nice-to-haves

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 tasks such as object detection, semantic or instance segmentation, or change detection, ideally applied to overhead imagery.
For all other states, we use geographic cost of labor as an input to develop market-driven ranges for our roles, and as such, each location where we hire may have a different range.
The date of posting can be found on Vantor s Career page at the top of each job posting.
To apply, submit your application via Vantor s Career page.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

gomachine learningmlci/cdpythonsqlai

Platform: workday
Effort: long

Benefits

Benefits detected in the listing.

Vision

401(K)