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Carnegie Mellon University

University training problem solvers and innovators

Autonomy Engineer

Robotics & Autonomous SystemsUpdated on Nov 14
Full-timeNo salary listed

About the Job

Requirements

  • A BS in Computer Science or a related discipline with eight years of experience, an MS in the same fields with five years of experience, or a PhD in Computer Science with two years of experience.
  • Be willing to work onsite five days per week at the SEI office in Pittsburgh, Pennsylvania, or Arlington, Virginia.
  • Be flexible to travel occasionally to other SEI offices in Pittsburgh and Washington, DC, sponsor sites, conferences, and offsite meetings; moderate travel of 25% outside the home location is expected.
  • Be eligible to obtain and maintain a Department of War security clearance, subject to a background investigation.
  • Have extensive research or engineering experience in applied autonomy and artificial intelligence, including tools, techniques, algorithms, software, or programming languages for deep learning, reinforcement learning, statistics, sensors and sensor fusion, planning, computer vision, or related areas.
  • Have applied systems engineering principles and collaborated across multidisciplinary project teams.
  • Have supported multiple phases of the engineering lifecycle and understand the requirements for successful deployment and operation of complex systems.
  • Have deep experience using simulators for development, machine-learning model training, and evaluation supporting uncrewed vehicle use cases.
  • Understand current modeling techniques for building digital-twin 3D objects and environments, and have addressed marine, land, or space domain challenges including sensor performance and collision meshes.
  • Have experience with physics-based simulators such as NVIDIA Isaac Sim.
  • Have a strong understanding of robotics principles and design techniques for air-, sea-, or land-based vehicles, and experience applying machine learning in these domains.
  • Understand autonomy-related challenges and areas including sensor fusion, navigation, object search and tracking, collision avoidance, multi-agent collaboration, and human-machine teaming.
  • Understand machine-learning principles and have experience applying machine-learning techniques to real-world problems, with a track record of successful implementations.
  • Have designed and implemented complex machine-learning functions and architectures tailored to specific autonomous systems.
  • Be familiar with simulation environments and their role in training and testing machine-learning models.
  • Have designed and conducted system-evaluation activities for machine-learning components to assess operational fit and readiness.
  • Have experience with model-experimentation software such as MLflow or Weights & Biases for model development and selection.
  • Have strong software-development experience and be able to design and implement software and systems resources for packaging and managing requirements for AI and machine-learning prototypes.
  • Use tools such as Docker to manage software resources and pipeline orchestration.
  • Have strong written and verbal communication skills and be able to interact collaboratively and diplomatically with customers and colleagues, understand an effort’s goals and direction while attending to detail, and present complex ideas to people without deep subject-area knowledge.
  • Be able to meet deadlines while multitasking under pressure and with shifting priorities.
  • Be able to learn new procedures, techniques, and approaches, and connect research and engineering with practical challenges.
  • Possess broad technical interests and deep knowledge of a field such as machine learning, autonomy and adaptive systems, or data analytics.

Responsibilities

  • Identify, shape, apply, conduct, and lead engineering research aligned with critical U.S. government needs.
  • Enhance simulation capabilities and apply simulation tools to support autonomy-related projects.
  • Work with and lead interdisciplinary teams to turn research results into prototype operational capabilities for government customers and stakeholders.
  • Conduct and lead novel prototyping in applied artificial intelligence, focusing on machine learning in autonomy and uncrewed systems across multiple domains.
  • Work with AI Division leaders and colleagues to plan, develop, and carry out an overall research and engineering strategy, and influence the national research and engineering agenda regarding future technology.
  • Participate on teams of software developers, researchers, designers, and technical leads.
  • Build relationships and collaborate with researchers, government customers, and other stakeholders to understand challenges, needs, potential solutions, and research and engineering directions.
  • Mentor and teach others, participate in software and other design sessions, and share knowledge across the SEI AI Division.

Desired Qualifications

  • Have a track record of synthesizing lessons learned from research or engineering activities for publication and demonstrate research and engineering integrity through contributions such as published research, code, models, data, software applications, or technical perspectives.
  • Be familiar with technical challenges and emerging trends in computing and information science, and aware of opportunities in industry and government.
  • Have led technical projects, collaborated across research teams, and mentored other researchers.
  • Have formulated and delivered successful research and engineering proposals to funding agencies and led the resulting projects.
  • Have worked with or be familiar with Navy, Marine Corps, Air Force, Army, Space Force, DARPA, IARPA, service laboratories, or other government research sponsors.
  • Have experience building applications on cloud platforms such as Azure, AWS, or Google Cloud Platform.

About the Company

Carnegie Mellon University

University training problem solvers and innovators

What Carnegie Mellon University does: It provides higher education and research across a wide range of fields, especially technology, engineering, sciences, and the arts, helping students become ready to enter the workforce and pursue innovative work. How its products work: It offers degree programs (bachelor’s, master’s, doctoral) and professional schools where students learn through classes, labs, projects, research opportunities, and collaborations with industry and the community. How it differentiates from competitors: CMU combines strong strengths in STEM with arts and design, interdisciplinary programs, and active collaboration with industry partners, all supported by a culture that emphasizes hands-on problem solving and real-world impact. What the goal is: To train capable graduates who can solve real problems, drive innovation, and contribute to technology, the arts, and society in meaningful ways.

Company size
11-50
Company stage
Not listed
Total funding
Not listed
Headquarters
Pittsburgh, PA
Founded
2018

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