Kitware
Machine Learning Engineer
About this role
Kitware seeks a Machine Learning Engineer to develop and deploy AI/ML solutions spanning computer vision, NLP, and generative AI technologies. You'll work on cutting-edge research projects for government agencies and commercial clients, contributing to open-source platforms and solving real-world problems through field collaboration and live demonstrations.
What you'll do
- Design and implement machine learning models for computer vision, NLP, and vision-language applications
- Collaborate with customers on dynamic, real-world AI problem-solving
- Contribute to open-source AI platforms including XAITK, NRTK, and GeoWATCH
- Participate in field tests and customer site demonstrations
- Apply state-of-the-art AI approaches to government and commercial projects
- Support research and development efforts for government R&D agencies
What they're looking for
- Machine learning and deep learning frameworks
- Computer vision and image processing
- Natural language processing
- Python or similar ML programming languages
- Generative AI technologies
- Open-source software development
- Data extraction from multiple sources
- Algorithm development and optimization
Benefits
- Direct collaboration with premier government agencies (DARPA, IARPA, AFRL, etc.)
- Customer site visits and field test participation
- Opportunity to contribute to impactful open-source projects
- Work on cutting-edge AI research and development
- Exposure to diverse real-world applications
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Kitware
Kitware develops innovative AI and machine learning software solutions, including computer vision, NLP, and generative AI technologies, often deployed for government agencies and commercial clients. The company is hiring Software Engineers and Machine Learning Engineers to work on cutting-edge research projects, open-source platforms, and real-world applications while collaborating with technical experts and customers.
- Website
- kitware.com
Likely interview questions
- Can you describe your experience with computer vision or NLP projects, and how you've applied state-of-the-art approaches to real-world problems?
- Tell us about a time you worked with multi-modal data sources (images, video, text, audio). How did you extract actionable insights from them?