Machine Learning II

Worker Type

Regular

Machine Learning Engineer II will have the opportunity to interact with R&D Group to develop a variety of innovative computer vision detection, classification, localization, and tracking solutions for defense and commercial applications. These development efforts will generally involve small, focused design teams which will require a senior machine learning engineer to use a range of skills and tools 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 detecting, 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 identify differences in data distribution that could affect performance.
• 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.
• Manage available resources such as hardware, data, and personnel so that deadlines are met.
• Analyze the ML algorithms to solve a given problem and rank them by their success probability.
• Deploy the model in the real world; verify data quality and/or ensure it via data cleaning.
• Analyze the errors of the model and design 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.
• Work on problems of moderate scope where analysis of situations or data requires a review of a variety of factors; exercise judgment within defined procedures and practices to determine appropriate action.
• Other duties as assigned.

• BS in Computer Vision and Machine Learning is required or an equivalent combination of education, training, and experience with qualifications in one 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.
• 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.
• Can 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.

• Abil…