As a senior machine learning engineer in the AI for Autonomy Lab at SEI’s AI Division, you will lead and conduct engineering research to address critical U.S. government needs by developing innovative solutions for autonomy systems. Your day-to-day responsibilities include hands-on prototyping with interdisciplinary teams, strategic planning, and collaboration with stakeholders to understand challenges and develop tailored machine learning functions. You will work on complex projects involving deep learning, reinforcement learning, computer vision, and robotics principles, using tools like Docker and cloud platforms such as AWS or Azure. With a background in applied AI and extensive experience in autonomy systems, you must be adept at test and evaluation methodologies and possess strong communication skills to interact effectively with diverse teams. This role requires a BS/MS/PhD in Computer Science along with relevant years of experience, and the ability to obtain a Department of War security clearance.
Skills
Python
Docker
AWS
Azure
Google Cloud Platform
MLFlow
Weights & Biases
CI/CD
PostgreSQL
Kubernetes
Terraform
RFID
Computer Vision
Reinforcement Learning
Deep Learning
Sensor Fusion
Navigation
Multi-Agent Systems
Human-Machine Teaming
What you'll do
Develop and lead interdisciplinary teams to transform research into operational AI prototypes for government clients.
Conduct novel prototyping in applied AI, focusing on machine learning for autonomy and uncrewed systems.
Plan and execute an engineering strategy with division leaders to influence national technology agendas.
Mentor team members by sharing technical insights and participating in design sessions.
Design and implement complex machine learning functions tailored to specific autonomous system requirements.
What we're looking for
BS in Computer Science or related field with 8+ years experience; MS with 5+ years; PhD with 2+ years.
Profound understanding and application of machine learning principles to real-world problems, including design and implementation of complex ML functions.
Strong background in robotics and autonomy for air, sea, or land-based vehicles, applying ML within these domains.
Experience designing and conducting test and evaluation activities for ML components using model experimentation software like MLFlow.
Expertise in full-stack AI/ML implementation, including development experience with cloud platforms and pipeline orchestration tools.
Excellent communication skills to collaborate effectively with multi-disciplinary teams and present complex ideas clearly.
Market check
Salary context
This listing doesn't show a salary. Similar roles on FindRole typically pay
$171,100–$244,900.
Peer median band
$171,100–$244,900
Median floor and ceiling across peers.
Typical midpoint (25–75%)
$174,303–$248,721
Middle half of comparable postings.
Based on 240 comparable postings.*
* 240 is the maximum number of comparable postings sampled.
Employer
About Carnegie Mellon University
Carnegie Mellon University is a leading private research university in Pittsburgh, Pennsylvania, internationally recognized for programs in computer science, engineering, business, the arts, and artificial intelligence. Industry: Higher Education & Research
Carnegie Mellon University currently has
36 open roles
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Python
TensorFlow
PyTorch
scikit-learn
MATLAB
C++
signal processing
wireless communication
MIMO
OFDM
SDRs
GPU acceleration
embedded machine learning
real-time systems
adaptive modulation
beamforming
cognitive radio techniques
3GPP
IEEE 802.11/15
military waveforms