Machine Learning Systems Research Intern at Red Hat working on AI inference and model optimization techniques. Collaborating with experts in the field while gaining hands - on experience in applied ML research.
About the role
- Machine Learning Engineer II developing innovative computer vision solutions for defense and commercial applications. Working on detection, classification, localization, and tracking with emphasis on algorithm integration and validation.
Responsibilities
- Support development of computer vision and machine learning algorithms capable of detection, classifying, localizing, and tracking objects-of-interest from a group 1 UAV using the existing gimballed camera payload
- Write and test software to support the integration of machine learning algorithms into aircraft (such as autopilots, payloads, or other functional components) or other robotic systems.
- Explore and visualize data to gain an understanding of it, then identifying differences in data distribution that could affect.
- Implement Machine Learning systems and validate designs through a series of purpose-designed experiments
- Create objectives and develop models that help to achieve them, along with metrics to track their progress
- Perform analysis tasks using AeroVironment and industry developed tools
- Managing available resources such as hardware, data, and personnel so that deadlines are met
- Analyze the ML algorithms to solve a given problem and ranking them by their success probability Performance when deploying the model in the real world; Verify data quality, and/or ensure it via data cleaning
- Analyze the errors of the model and designing strategies to overcome them
- Study and transform data science prototypes; Research and implement appropriate ML algorithms and tools
- Select appropriate datasets and data representation methods; Run machine learning tests and experiments
- Works on problems of moderate scope where analysis of situations or data requires a review of variety of factors. Exercises judgment within defined procedures and practices to determine appropriate action
Requirements
- BS in Computer Vision and Machine Learning is required or equivalent combination of education, training, and experience
- Minimum of 2 – 5 years' relevant experience
- Familiarity with C/C++ and Matlab required
- Proficiency with a deep learning framework such as TensorFlow or Keras
- Proficiency with Python and basic libraries for machine learning such as scikit-learn and pandas
- Expertise in visualizing and manipulating big datasets
- Proficiency with OpenCV
- Familiarity with Linux
- Ability to select hardware to run an ML model with the required latency
- Computational statistics
- Mathematical optimization
- Data mining
- Exploratory data analysis
- Predictive analytics
Benefits
- medical
- dental
- vision
- 401K with company matching
- a 9/80 work schedule
- paid holiday shutdown
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