Machine Learning Engineer - Autonomy Lab

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

• Actively 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, possible solutions, and research and engineering directions.

Mentoring

• 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.
• 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.

Knowledge, Skills, and Abilities

• Deep Technical Knowledge: Extensive research or engineering activities in applied machine learning 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; understanding of requirements for successful deployment and operation of complex systems.
• Machine Learning: Profound understanding of machine learning principles; experience in applying machine learning techniques to real-world problems; designing and implementing complex machine learning functions and architectures tailored to specific autonomous systems; familiarity with simulation environments and their role in training and testing machine learning models.
• Robotics & Autonomy: Strong understanding of robotics principles and design techniques for air, sea, or land-based vehicles; experience applying machine learning within these domains; understanding of related implications and challenges; experience in areas such as sensor fusion, navigation, object search/tracking, collision avoidance, multi-agent collaboration, and human-machine teaming.
• Test & Evaluation: Designing and conducting test and 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; frequent use of 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; ability to interact collaboratively and diplomatically with customers and colleagues; ability to present complex ideas to people who may not have a deep understanding of the subject area.
• Dedication: Ability to 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; quick learning of new procedures, techniques, and approaches; forward-looking and connecting 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 highest level of research and engineering integrity; publishing research, code (e.g., models, data, software applications), or technical perspectives.
• Familiarity with Emerging Trends and Opportunities: Familiarity with technical challenges and emerging trends in computing and information science; awareness of opportunities in industry and government.
• Technical Leadership: Leading technical projects; collaborating across research teams and mentoring other researchers; formulating and delivering successful research and engineering proposals to funding agencies and leading the resulting projects.
• Government Projects: Working or being familiar with Navy, Marine, Air Force, Army, Space Force, DARPA, IARPA, Service Labs, or other government research sponsors.

Benefits

• Comprehensive medical, prescription, dental, and vision insurance.
• A generous retirement savings program with employer contributions.
• Tuition benefits.
• Ample paid time off and observed holidays.
• Life and accidental death and disability insurance.
• Pittsburgh Regional Transit bus pass.
• Family Concierge Team to help navigate childcare needs.
• Access to fitness center.

Additional Perks

• Free Pittsburgh Regional Transit bus pass.
• Family Concierge Team to help navigate childcare needs.
• Access to fitness center.

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

Please visit “Why Carnegie Mellon” to learn more about becoming part of an institution inspiring innovations that change the world. Click here to view a listing of employee benefits.

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