Senior AI Engineer

Scout AI

Senior AI Engineer developing multimodal foundation models for defense at Scout AI. Influencing the coordination of multiple robots in complex missions.

Posted 7/8/2026full-timeRemote • California • 🇺🇸 United StatesSenior💰 $200,000 - $400,000 per yearWebsite

Tech Stack

Tools & technologies

PythonPyTorch

About the role

Key responsibilities & impact

Design, train, and evaluate multimodal foundation models that enable multi-robot mission execution
Drive model development decisions including model architectures, data mixtures, curriculum design, and training recipes informed by rigorous experimentation
Curate and generate large-scale training datasets from both synthetic and real-world data engines
Develop memory, communication, planning, and tool-use capabilities for AI agents operating across teams of robots
Be obsessed with evaluation: design benchmarks, metrics, and testing methodologies that enable rapid iteration across the team
Build and improve simulation environments targeted for synthetic data generation, evaluation, and reinforcement learning
Translate foundational research into deployable, real-time perception and decision-making systems
Collaborate across engineering, robotics, and mission teams to integrate AI systems with onboard autonomy stacks
Conduct field trials and mission operations to validate system performance under real-world constraints

Requirements

What you’ll need

6+ years of hands-on experience building and deploying AI models, including 2+ years working with multimodal models or agentic AI systems
Proficiency in Python, PyTorch, and modern machine learning infrastructure
Experience training, finetuning, and evaluating large-scale deep learning models using distributed compute infrastructure
Demonstrated experience improving model performance through data curation, training strategy, evaluation design, and rigorous experimentation
Solid grasp of modern model training techniques including SFT, DPO, RLVR
Demonstrated ability to take research from prototype to product in fast-moving environments
BS, MS, or PhD in Computer Science, Engineering, Mathematics, Physics, or related technical field, or equivalent practical experience. Advanced graduate research in AI, robotics, or machine learning is a plus.
Bonus: Experience building closed-loop simulation, evaluation, or reinforcement learning environments for agentic or physical AI systems
Must be a U.S. Person due to required access to U.S. export controlled information or facilities.

Benefits

Comp & perks

Competitive compensation package including base salary and bonus
Meaningful equity
Premium medical, dental, and vision plans with $0 paycheck contribution
Competitive PTO and company holiday calendar
Unlimited AI tokens
Catered lunch daily and fully stocked kitchen
EV charging
Relocation assistance (depending on role eligibility)

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

Multimodal Model DevelopmentData CurationTraining StrategyEvaluation DesignReinforcement LearningDistributed Compute InfrastructureSimulation Environment DevelopmentBenchmark DesignDecision-Making SystemsAgentic AI Systems

Soft Skills

CollaborationProblem-SolvingRigorous Experimentation