Machine Learning Engineer II

Summary

The Machine Learning Engineer II will have the opportunity to interact with the R&D Group to develop a variety of innovative computer vision detection, classification, localization, and tracking solutions for defense and commercial applications. Development efforts will generally be small focused design teams which require a senior machine learning engineer to use a range of skills across traditional engineering, computer science, and mathematical disciplines including computer vision, machine learning, optimization, deep convolutional neural networks, and visual tracking.

This position will work on a variety of stages of development including requirements definition, concept design, prototyping, detailed design, test and evaluation and validation and verification testing.

• 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 Aero Vironment 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
• Other duties as assigned

• BS in Computer Vision and Machine Learning is required or equivalent combination of education, training, and experience - with qualifications in any of the following fields:
  Mathematics, Optimization, Computer Science/Engineering, Electrical Engineering, Aerospace, or Mechanical Engineering
• Minimum of 2 – 5 years  relevant experience
• Familiarity with C/C++ and Matlab required
• Familiarity with office software and computer-based productivity tools
• Demonstrated ability to troubleshoot complex systems

• Proficiency with a deep learning framework such as Tensor Flow 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

• Works well within defined requirements to complete tasks under moderate supervision
• Must be a team player and collaborate effectively
• Excellent verbal and written skills
• Has effective problem-solving, analytical and interpersonal skills
• Able to excel in a fast-paced, deadline-driven environment, where small teams share a broad variety of duties
• Displays strong initiative and drive to accomplish goals and meet company objectives
• Takes ownership and responsibility for current and past work products
• Is committed to learning from mistakes and driven to improve and enhance performance of oneself, others, and the company

• Ability to work in an office and manufacturing…