Software Engineering Institute | Carnegie Mellon University · 3 days ago
Machine Learning Engineer - Autonomy Lab - 2024072
Pittsburgh, PA
Full-time
Onsite
Senior Level
5+ years expCarnegie Mellon University's Software Engineering Institute is focused on advancing applied artificial intelligence and engineering for national security. The Machine Learning Engineer will lead research and prototyping efforts to develop AI capabilities for autonomy systems that address critical government needs.
ComputerCyber SecurityEducationSoftware
No H1B
Security Clearance RequiredU.S. Citizen OnlyHiring Manager
Bill Scully
Responsibilities
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
Qualification
Required
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
You must be able and willing to work onsite at an SEI office in Pittsburgh, PA or Arlington, VA 5 days per week
Flexible to travel to other SEI offices, 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
Deep Technical Knowledge: You have performed extensive research or engineering activities in applied machine learning and artificial intelligence. You have worked with tools, techniques, algorithms, software, and programming languages for deep learning, reinforcement learning, statistics, sensors and sensor fusion, planning, computer vision, or related areas. In addition, you have demonstrated applying systems engineering principles and collaborated across multi-disciplinary project teams. You have supported multiple phases of the engineering lifecycle and understand the requirements for successful deployment and operation of complex systems
Machine Learning: You have profound understanding of machine learning principles and have experience in applying machine learning techniques to real-world problems, showcasing a track record of successful implementations. You have designed and implemented complex machine learning functions and architectures tailored to specific autonomous systems. You are familiar with simulation environments and their role in training and testing machine learning models
Robotics & Autonomy: You have a strong understanding of robotics principles and design techniques for air, sea, or land-based vehicles. You have experience applying machine learning within these domains and understand the related implications and challenges. Your experience includes areas such as sensor fusion, navigation, object search/tracking, collision avoidance, multi-agent collaboration, and human-machine teaming
Test & Evaluation: You have designed and conducted test and evaluation activities for ML components to assess operational fit and readiness. You have experience working with model experimentation software, such as MLFlow or Weights & Biases for rigorous model development and selection
Applied Full-Stack Implementation: You have strong development experience and can design and implement software and systems resources for packaging and managing requirements for AI and ML prototypes. You frequently use tools like Docker to manage software resources and pipeline orchestration. You may have experience building applications in cloud platforms (Azure, AWS, Google Cloud Platform)
Communication and Collaboration: You have strong written and verbal communication skills and can interact collaboratively and diplomatically with customers and colleagues. You grasp the big picture, direction, and goals of an effort while focusing great attention to detail. You can present complex ideas to people who may not have a deep understanding of the subject area
Dedication: You can meet deadlines while multi-tasking–sometimes under pressure and with shifting priorities
Creativity and Innovation: You are creative and curious, and you are inspired by the prospect of collaborating with premier members of the technical staff and other visionaries at Carnegie Mellon and other universities and organizations. You quickly learn new procedures, techniques, and approaches. You are forward-looking and can connect research and engineering with practical challenges
Knowledge and Learning: You possess broad technical interests along with a deep knowledge of a particular field such as machine learning, autonomy and adaptive systems, or data analytics
Preferred
Thought Leadership and Publications: You have a track record of synthesizing lessons learned from research or engineering activities for publication. You have a reputation for the highest level of research and engineering integrity. You have demonstrated contributions and have published research, code (e.g., models, data, software applications), or technical perspectives
Familiarity with Emerging Trends and Opportunities: You are familiar with technical challenges and emerging trends in computing and information science, and you are aware of opportunities in industry and government
Technical Leadership: You have led technical projects and have experience collaborating across research teams and mentoring other researchers
Proposals: You have formulated and delivered successful research and engineering proposals to funding agencies and led the resulting projects
Government Projects: You have worked or are familiar with Navy, Marine, Air Force, Army, Space Force, DARPA, IARPA, Service Labs, or other government research sponsors
Company
Software Engineering Institute | Carnegie Mellon University
At the SEI, we research complex software engineering, cybersecurity, and AI engineering problems; create and test innovative technologies; and transition maturing solutions into practice.
501-1000 employees
Funding
Current Stage
Late StageLeadership Team
Paul Nielsen
Director and CEO
Christopher Herr
Senior Engineer/Cybersecurity Exercise Developer and Trainer
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