AI/ML Engineer

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. We are seeking an AI/ML Engineer to develop and maintain autonomous planning, scheduling, and optimization systems for advanced Earth Observation satellite operations. You will be joining an onsite team located in the Herndon, VA office with core in‑office days on Tuesday, Wednesday, and Thursday, with occasional additional days to support customer or mission‑related activities. To be eligible for this position, you must be a U.S. Person, defined as a U.S. citizen, permanent resident, asylee, or refugee. 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). What You’ll Do Design and implement scalable reinforcement learning, 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 Success Looks Like (12–18 Months) Your modernized scheduling and decision‑support system is actively used by planners in daily operations. Teams can evaluate alternative planning strategies with measurable outcomes based on your models. Early‑stage learning systems (optimization / RL) are improving planning performance over time. Minimum Qualifications Bachelor’s degree in Computer Science, Data Science, Aerospace Engineering, Applied Mathematics, Physics, or a 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 and evaluation pipelines for ML systems Preferred 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 Pay Transparency Starting pay for this role will fall within the listed range: $137,000.00 – $182,000.00 for the Washington, DC metropolitan area. For other states, geographic cost of labor is used to develop market‑driven ranges. Candidates who meet the minimum requirements should not expect compensation at the top of the range; final offers will be based on experience, qualifications, and alignment with the role. Benefits Vantor offers a competitive total rewards package that includes a robust 401(k) with company match, mental health resources, and unique perks such as student loan repayment assistance, adoption reimbursement, and pet insurance. EEO Policy Vantor is an equal opportunity employer committed to an inclusive workplace. 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. #J-18808-Ljbffr