Senior Machine Learning Engineer (Geospatial AI)

Location: Hybrid role based in Arlington, Virginia, with three days per week in the office. Candidates must be located in the Washington, DC metro area or able to commute to Arlington. Ability to obtain and maintain US Security Clearance is required.

Salary: $160,600–$200,800 USD annual base salary, plus potential short- and long-term incentives, bonus, and equity.

Company

hirify.global designs, builds, and operates a large constellation of imaging satellites and provides cloud-based satellite data for commercial, environmental, humanitarian, Defense, and Intelligence applications.

What you will do

• Develop novel machine learning algorithms and models for Defense and Intelligence applications.
• Build computer vision, time series, embeddings-based, change-detection, and object-detection solutions using satellite data.
• Optimize models for high-throughput inference at continental and global scales.
• Integrate machine learning preprocessing and inference pipelines with software engineering platforms.
• Collaborate with product managers, data scientists, and software engineers to define requirements and iterate on algorithm designs.
• Establish testing, validation, monitoring, and reliability frameworks for deployed models.

Requirements

• 10+ years of relevant experience, including 6+ years in machine learning.
• Expertise in data science, time series methods, computer vision, embeddings, and neural network training and optimization.
• Experience with large datasets, geospatial libraries, and PyTorch or TensorFlow.
• Strong Python development skills and experience with Git, testing, and CI/CD.
• Experience deploying and monitoring models with Docker, Kubernetes, or similar technologies, plus AWS or GCP experience.
• Must be able to work from the Arlington office three days per week, commute from the Washington, DC metro area, and obtain and maintain US Security Clearance.

Nice to have

• Knowledge of remote sensing, satellite imagery, or related geospatial domains.
• Experience with coordinate reference systems, geometry manipulation, GeoTIFF, GeoJSON, and other geospatial formats.
• Experience building geospatial or sensor-driven data products from scratch.
• Familiarity with model compression, GPU optimization, or distributed training pipelines.

Culture & Benefits

• Medical, dental, and vision plans, with a health savings account and company contribution.
• Paid time off, holidays, company-wide days off, and 16 weeks of paid parental leave.
• Wellness and employee assistance programs.
• Home office, phone, internet, tuition, and learning reimbursements.
• Equity, commuter benefits for local office employees, and paid volunteering time off.
• People-centric culture focused on belonging, inclusion, and humanitarian impact.