Robotics and Machine Learning Engineering Intern

Lockheed Martin•Stratford, CT

23h•$31,616 - $77,788•Onsite

About The Position

By bringing together people that use their passion for purposeful innovation, at Lockheed Martin we keep people safe and solve the world's most complex challenges. Our people are some of the greatest minds in the industry and truly make Lockheed Martin a great place to work. With our employees as our priority, we provide diverse career opportunities designed to propel development and boost agility. Our flexible schedules, competitive pay, and comprehensive benefits enable our employees to live a healthy, fulfilling life at and outside of work. At Lockheed Martin, we place an emphasis on empowering our employees by fostering innovation, integrity, and exemplifying the epitome of corporate responsibility. Your Mission is Ours. The Flight Controls and Autonomy team is currently seeking highly motivated technology pioneers with a desire to steer and lead the Autonomy industry. Successful candidates must be willing and able to work on highly complex challenging problems, leading to world-changing technological breakthroughs. Sikorsky autonomy team is at the forefront of developing cutting-edge autonomous software for small Uninhabited Aerial Systems (UAS) and full-scale air vehicles. As a leading innovator in the aviation industry, we are seeking motivated summer interns to contribute to the advancement of autonomous technologies. Design and implement advanced deep learning architectures by seamlessly integrating Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Transformers for tasks such as classification, object detection, depth estimation, and semantic segmentation to enhance perception and decision-making capability of aerial vehicles. · Explore and implement cutting-edge techniques in Reinforcement Learning (RL) and Imitation Learning (IL) for aerial robotics, contributing to the autonomous navigation and decision-making of our systems.

Requirements

Enrolled in undergraduate or graduate program in computer science, engineering, robotics, or artificial intelligence and machine learning.
Coursework on deep learning, machine learning and robotics.
Hands-on experience with deep learning architectures for vision processing and Reinforcement Learning (RL). This includes Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Transformers applied to aerial robotics for autonomous navigation, perception, and decision making.
Proficient in Python and experienced in neural network programming frameworks such as Pytorch.

Nice To Haves

Experience with classical motion planning and computer vision algorithms.
Familiarity with C/C++ programming language.

Responsibilities

Design and implement advanced deep learning architectures by seamlessly integrating Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Transformers for tasks such as classification, object detection, depth estimation, and semantic segmentation to enhance perception and decision-making capability of aerial vehicles.
Explore and implement cutting-edge techniques in Reinforcement Learning (RL) and Imitation Learning (IL) for aerial robotics, contributing to the autonomous navigation and decision-making of our systems.