- Research, design, and implement machine learning models and algorithms for computer vision tasks, including object detection, image classification, and segmentation.
- Train and fine-tune convolutional neural networks (CNNs) using deep learning frameworks such as TensorFlow, PyTorch, or Keras
- Research, design, and implement machine learning models for autonomous systems with a focus on monitoring system health and planning future maneuvers to achieve prioritized objectives
- Collaborate with domain experts to collect and preprocess data for training and evaluation of ML models, ensuring data quality and integrity
- Conduct comprehensive literature reviews to stay abreast of the latest advancements in AI/ML, computer vision, and predictive maintenance, and apply state-of-the-art techniques to enhance the company's solutions
- Conduct performance evaluation and optimization of ML algorithms to meet accuracy, latency, and scalability requirements
- Must be eligible to hold a clearance.
- Experience training and deploying predictive maintenance models OR experience with machine learning enabled autonomous systems is REQUIRED
- Bachelor's degree or higher in Computer Science, Engineering, Mathematics, or related field.
- Strong proficiency in Python programming and deep learning libraries such as TensorFlow, PyTorch, or Keras
- Familiarity with predictive maintenance techniques, time series analysis, and anomaly detection algorithms
- Excellent problem-solving skills, analytical thinking, and attention to detail
- Strong communication and collaboration skills, with the ability to work effectively in a team environment
- 5+ years experience
- Master's or PhD degree in Computer Science, Artificial Intelligence, or related field
- Experience with training and deploying networks trained on synthetic datasets and demonstrated understanding of techniques to bridge the domain gap to work with real datasets
- Experience with edge computing and deploying ML models to resource-constrained environments.
- Hands-on experience with computer vision frameworks and tools such as OpenCV
- Hands on experience with autonomous systems
- Fundamental understanding of space systems, orbital dynamics, and spacecraft operations
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AI/ML Engineer - Reston, United States - SCOUT
Description
AI/ML Engineer (Predictive Maintenance or Autonomy Expertise REQUIRED)Scout is building a new way to see and operate in space: with a new paradigm of data empowering every satellite to make space safer. We are a rapidly-growing team; we are deploying real solutions to orbit; and our work will transform the face of spaceflight. We are looking for people that bring excitement and energy to our organization, are curious and eager to learn, and want to help drive our programs forward.
As an AI/ML Engineer, you will play a crucial role in the design and implementation of our advanced algorithms supporting spacecraft autonomy and space object detection, tracking, and classification from optical payloads. This position is dependent on a contract award.
Responsibilities:
Our positions are based in the Reston, Virginia area, with much of our team operating in a hybrid or remote fashion. Our preference is for candidates in or around this area (or willing to relocate) as we scale our facilities and engineering team and provide more opportunities to work and collaborate in-person. Remote employees will be required to travel for onsite work and in-person meetings.
Scout Inc. does not discriminate in employment on the basis of race, color, religion, sex (including pregnancy and gender identity), national origin, political affiliation, sexual orientation, marital status, disability, genetic information, age, membership in an employee organization, retaliation, parental status, military service, or other non-merit factor. To conform to US Government space technology export regulations, applicants must be a US citizen, lawful permanent resident of the US, a protected individual as defined by 8 USC 1324b(a)(3), or eligible to obtain the required authorization from the US Department of State.
#hybrid #remote
