Autonomy Engineer

Solution Development

You’ll work with and lead interdisciplinary teams to turn research results into prototype operational capabilities for government customers and stakeholders.

Hands-on Prototyping

You’ll conduct and lead novel prototyping in applied artificial intelligence with a focus on machine learning in autonomy and uncrewed systems (multi-domain).

Strategy

You’ll work with AI Division leaders and colleagues to plan, develop, and carry out an overall research and engineering strategy, and to influence the national research and engineering agenda regarding future technology.

Collaboration

You'll actively participate on teams of software developers, researchers, designers, and technical leads. You'll build relationships and collaborate with researchers, government customers, and other stakeholders to understand challenges, needs, possible solutions, and research and engineering directions.

Mentoring

You'll contribute to improving the overall technical capabilities of the team by mentoring and teaching others, participating in design (software and otherwise) sessions, and sharing insights and wisdom across the SEI AI Division.

Requirements

• BS in Computer Science or related discipline with eight (8) years of experience; MS in the same fields with five (5) years of experience; PhD in Computer Science with two (2) years of experience.
• This position is based onsite 5 days per week at SEI's offices in either Pittsburgh, PA or Arlington, VA.
• Flexible to travel to other SEI offices in Pittsburgh and Washington, DC, sponsor sites, conferences, and offsite meetings on occasion.
• Moderate (25%) travel outside of your home location.
• You will be subject to a background investigation and must be eligible to obtain and maintain a Department of War security clearance.

Knowledge, Skills, and Abilities

• Deep Technical Knowledge: Extensive research or engineering activities in applied autonomy and artificial intelligence; extensive experience with tools, techniques, algorithms, software, and programming languages for deep learning, reinforcement learning, statistics, sensors and sensor fusion, planning, computer vision, or related areas; systems engineering principles and collaboration across multi-disciplinary project teams; multiple phases of the engineering lifecycle and requirements for successful deployment and operation of complex systems.
• Modeling & Simulation: Deep experience using simulators for development, ML model training, and evaluation activities supporting uncrewed vehicle use cases; current state of the art modelling techniques to build digital twin 3D objects and environments; challenges related to marine, land, or space domains including sensor performance and collision meshes; physics-based simulators such as NVIDIA’s Issac Sim.
• Robotics & Autonomy: Strong understanding of robotics principles and design techniques for air, sea, or land-based vehicles; experience applying machine learning within these domains and related implications and challenges; areas such as sensor fusion, navigation, object search/tracking, collision avoidance, multi-agent collaboration, and human-machine teaming.
• Machine Learning: Proven understanding of machine learning principles; experience in applying machine learning techniques to real-world problems; successful implementations; simulation environments and their role in training and testing machine learning models.
• System Evaluation: Designed and conducted system evaluation activities for ML components to assess operational fit and readiness; experience working with model experimentation software, such as MLFlow or Weights & Biases for rigorous model development and selection.
• Applied Full-Stack Implementation: Strong development experience; design and implement software and systems resources for packaging and managing requirements for AI and ML prototypes; tools like Docker to manage software resources and pipeline orchestration; experience building applications in cloud platforms (Azure, AWS, Google Cloud Platform).
• Communication and Collaboration: Strong written and verbal communication skills; interact collaboratively and diplomatically with customers and colleagues; grasp the big picture, direction, and goals of an effort while focusing great attention to detail; present complex ideas to people who may not have a deep understanding of the subject area.
• Dedication: Meet deadlines while multi-tasking–sometimes under pressure and with shifting priorities.
• Creativity and Innovation: Creative and curious; inspired by the prospect of collaborating with premier members of the technical staff and other visionaries at Carnegie Mellon and other universities and organizations; quickly learn new procedures, techniques, and approaches; forward-looking and connect research and engineering with practical challenges.
• Knowledge and Learning: Broad technical interests along with deep knowledge of a particular field such as machine learning, autonomy and adaptive systems, or data analytics.

Preferred Experience

• Thought Leadership and Publications: Synthesizing lessons learned from research or engineering activities for publication; reputation for the highest level of research and engineering integrity; published research, code (e.g., models, data, software applications), or technical perspectives.
• Familiarity with Emerging Trends and Opportunities: Familiar with technical challenges and emerging trends in computing and information science; aware of opportunities in industry and government.
• Technical Leadership: Led technical projects; collaborated across research teams and mentored other researchers.
• Proposals: Formulated and delivered successful research and engineering proposals to funding agencies and led the resulting projects.
• Government Projects: Worked or familiar with Navy, Marine, Air Force, Army, Space Force, DARPA, IARPA, Service Labs, or other government research sponsors.

Location

Arlington, VA, Pittsburgh, PA

Job Function

Software/Applications Development/Engineering

Position Type

Staff – Regular

Full time/Part time

Full time

Pay Basis

Salary

More Information

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Carnegie Mellon University is an Equal Opportunity Employer/Disability/Veteran.