AI/ML Engineer

Vantor • Herndon, VA

4d • $137,000 - $200,200 • Onsite

About The Position

Vantor is seeking an AI/ML Engineer to develop and maintain autonomous planning, scheduling, and optimization systems for advanced Earth Observation satellite operations. This role focuses on applying reinforcement learning (RL), operations research, and sequential decision-making techniques to optimize heterogenous satellite constellation collection plans. You will be joining an onsite team located in the Herndon, VA office with core in-office days on Tuesday, Wednesday, and Thursdays. Other days may occasionally be required to support customer or mission-related activities.

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
• Must be a U.S. Person, defined as a U.S. citizen, permanent resident, Asylee, or Refugee.

Nice To Haves

• 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

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

Benefits

• Robust 401(k) with company match
• Mental health resources
• Student loan repayment assistance
• Adoption reimbursement
• Pet insurance

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level