AI/ML Engineer

About the role

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.

Responsibilities

• Design and implement scalable reinforcement learning (RL), optimization, and decision-making algorithms for satellite sensor and constellation tasking and planning
• Build high-fidelity simulation and evaluation environments for training and validating autonomous planning strategies under real-world operational constraints
• Develop multi-objective optimization pipelines balancing coverage, revisit rate, latency, resource utilization, revenue, and mission success metrics
• Train, evaluate, and deploy ML and decision-making models in production environments using modern DevOps practices
• Collaborate with aerospace engineers, mission operators, software engineers, and product teams to translate mission requirements into deployable AI systems

Requirements

• Bachelor’s degree in Computer Science, Data Science, Aerospace Engineering, Applied Mathematics, Physics, or related field
• 5+ years of experience developing machine learning or optimization systems
• Strong programming skills with experience using modern ML frameworks such as PyTorch, TensorFlow, Scikit-learn, or JAX
• Experience with probabilistic modeling, uncertainty estimation, and Bayesian optimization algorithms
• Experience building training & evaluation pipelines for ML systems

Qualifications

• Experience with orbital mechanics, satellite systems, remote sensing, mission operations, and collection planning
• Strong software engineering fundamentals including testing, CI/CD, version-control, and containerized deployment
• Familiarity with GPU acceleration and distributed training infrastructure
• Experience with autonomous systems or multi-agent planning architectures is a plus

Skills

Not specified

Benefits

• Roth 401(k) with company match
• Mental health resources
• Student loan repayment assistance
• Affordable pet insurance
• Adoption reimbursement

Pay

The base pay for this position within the Washington, DC metropolitan area is: $137,000.00 - $182,000.00 - $200,200.00 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.

Schedule

Core in-office days are Tuesday, Wednesday, and Thursday. Other days may occasionally be required to support customer or mission-related activities.