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Ai Engineer Developer information
What is a 900000 AI job?
What is the difference between Ai Engineer Developer vs Data Scientist?
| Aspect | Ai Engineer Developer | Data Scientist |
|---|---|---|
| Required Credentials | Bachelor's in CS, AI, or related; programming skills; knowledge of ML frameworks | Bachelor's or higher in CS, Statistics, or related; strong analytical and statistical skills |
| Work Environment | Develops AI models, algorithms, and systems; often in tech or R&D teams | Analyzes data, builds models, and interprets insights; in analytics or research teams |
| Employer & Industry Usage | Tech companies, AI startups, R&D divisions | Finance, healthcare, marketing, and tech sectors |
While both roles involve working with data and machine learning, Ai Engineer Developers focus on building and deploying AI systems and algorithms, whereas Data Scientists analyze data to extract insights and inform decision-making. The roles often overlap but differ in primary responsibilities and skill emphasis.
What engineer makes 500,000 a year?
Which 3 jobs will survive AI?

Other
Medical, Dental, Vision, PTO
Re-posted 9 days ago
Job description
The future of defense will be decided by those who field intelligent machines at scale. At Scout AI, we're developing Fury, the first robotic foundation model for defense, to give U.S. forces overwhelming, adaptable, and autonomous power across every domain. Fury enables human operators to command fleets of robots through natural language, and empowers those machines to sense, decide, and act together as one. This mission will ask everything of us: urgency, precision, and relentless work.
The Role
We're looking for an AI Engineer to join the Fury Orchestration Team with a deep passion for developing and deploying multimodal foundation models that power autonomous teams of robots. Your work will directly influence how our system reasons, plans, remembers and coordinates across multiple robots to accomplish long-horizon missions. Depending on your background and interests, you'll contribute across the stack: model training and evaluation, reinforcement learning, evaluation and simulation, reasoning and memory architectures, multi-agent coordination, and edge inference optimization. Expect to rapidly prototype ideas against rigorous evaluations, test ideas on real robotic mission rollouts, and break new ground as we create the first robotic foundation model for defense.
We're a startup. You'll be moving fast, context-switching daily, and helping define the culture and process as we go. You'll have substantial ownership, influence over technical direction, and the opportunity to help build the future of autonomous defense systems from the ground up.
Responsibilities
- 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 e under real-world constraints
Qualifications
- 2+ 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 facilitie
Why Join Scout
- Work on the world's most important frontier, ensuring U.S. and allied dominance in the age of intelligent machines
- Be a core part of a team building the first defense-specific robotic foundation model
- Collaborate with some of the top engineers in autonomy, AI, and national security
- See your work deployed on real systems
- Help define the future of intelligent defense systems
- Backed by Draper Associates, Booz Allen Ventures, and other top investors
Benefits
- 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)