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From Home Embedded Machine Learning Jobs in Virginia

... from field tests, and developing advanced algorithms. MORSE's AI & ML work crosses modalities, and ... embedded system. You will be part of our team working to accelerate our US National Security ...

This role involves building and maintaining the complete ML lifecycle-spanning from data pipelines ... Embedded Linux and ROS experience * Defense/aerospace industry background * Additional Google Cloud ...

Machine Learning Engineer LOCATIONChantilly, VA 20151 CLEARANCETS/SCI Full Poly (Please note this ... From employee and family events to career-long support, we create a community you'll never want to ...

Machine Learning Engineer LOCATIONTysons, VA 22182 CLEARANCETS/SCI Full Poly (Please note this ... From employee and family events to career-long support, we create a community you'll never want to ...

Machine Learning Engineer LOCATION Reston, VA 20190 CLEARANCE TS/SCI Full Poly (Please note this ... From employee and family events to career-long support, we create a community you'll never want to ...

Machine Learning Engineer LOCATION Tysons, VA 22182 CLEARANCE TS/SCI Full Poly (Please note this ... From employee and family events to career-long support, we create a community you'll never want to ...

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From Home Embedded Machine Learning information

What jobs make 3000 a month without a degree?

In the field of embedded machine learning, entry-level roles such as remote data annotators, AI support specialists, or freelance machine learning assistants can earn around $3,000 per month without a degree, especially with relevant skills in programming, data handling, and familiarity with tools like Python or TensorFlow. These positions often require self-learning, online certifications, or prior experience working with embedded systems and AI models remotely.
What are the most commonly searched types of Embedded Machine Learning jobs in Virginia? The most popular types of Embedded Machine Learning jobs in Virginia are:
What cities in Virginia are hiring for From Home Embedded Machine Learning jobs? Cities in Virginia with the most From Home Embedded Machine Learning job openings:
Machine Learning Engineer

Machine Learning Engineer

MORSE Corp

Arlington, VA • On-site

Other

Posted 24 days ago


Job description

We are seeking a Machine Learning Engineer to join our team at MORSE. You will play a pivotal role in designing, implementing, and managing complex ML algorithms and systems, with a focus on computer vision (CV) and other types of data. You will be responsible for acquiring truth data, integrating algorithms, testing algorithms, combining algorithms, reviewing literature to stay on top of the latest-and-greatest methods, analyzing data from field tests, and developing advanced algorithms. MORSE's AI & ML work crosses modalities, and experience or interest in the fields of Large Language Models (LLM), audio analysis, computer vision, and advanced reasoning is a plus. You will work with MORSE's current team of engineers to transition algorithms to production, which may run on on-prem servers, on the cloud, or on a real-time embedded system. You will be part of our team working to accelerate our US National Security customers abilities to use natural language processing capabilities in mission-critical environments. 

Responsibilities: 
  • Develop, fine-tune, train, and optimize Computer Vision algorithms processing tasks such as object detection and tracking.  
  • Use MLOps tools for efficient experiment tracking, data management, and reproducibility 
  • Write robust, efficient, and maintainable code 
  • Track the latest advancements with machine learning research to bring new techniques and methodologies to MORSE 
  • Conduct experiments and perform rigorous evaluations to assess the effectiveness and efficiency of CV models 

Skills and Requirements: 
  • US CITIZENSHIP REQUIRED and the ability to obtain a U.S. Security Clearance 
  • Masters or Ph.D. in Computer Science, Computer Engineering, Data Science, Aerospace, Mathematics, Physics, or related field 
  • Proven experience in applying CV models, techniques, frameworks, and libraries to implement and fine-tune models 
  • Proven experience testing and validating the performance of AI technologies in real-world applications 
  • Proficiency in Python 
  • Experience with cloud platforms (AWS and Azure) 
  • Experience with Docker 
  • Experience with MLOps tools such as Airflow, MLFlow, AimStack, etc. 
  • Exceptional communication skills and the ability to work well with customers 
  • Understanding of Department of Defense requirements and standards is a plus