Project Description:

At Spaice, we specialize in developing AI-based software for in-orbit servicing, with a focus on perception, autonomous navigation on the edge, and robotics operations. One of the main challenges we address with our perception solutions is the 6 Degrees Of Freedom pose estimation of target satellites at various ranges, encompassing both translation and rotation relative to the chaser satellite.

Aligned with Spaice's commitment to staying at the forefront of technological advancements, we are seeking a research engineer intern. In this role, you will explore alternative methods, experiment with new architectures, and implement different training strategies to complement or enhance our existing pose estimation solutions. Guided by Spaice’s Research Scientists, your objective is to achieve improvements in precision and real-time computing on an edge computing platform, enabling precise tracking and positioning of satellites. Your contributions have the potential to directly impact Spaice's final perception pipeline.

Your responsibilities will involve working with diverse perception solutions tailored to meet specific requirements at varying distances, ranging from kilometers away to docking with target satellites. This includes dealing with different sensing modalities and various types of data, such as images of different natures, point clouds, or meshes.

As a Machine Learning Research Engineer Intern, you will:

• Read and comprehend state-of-the-art computer vision papers.

• Design, code, and train various deep learning architectures using PyTorch.

• Operate with cloud computing, specifically AWS instances.

• Deploy ML models on edge computers.

• Optimize perception pipelines for real-time execution.

• Find out more about SPIN and explore FAQs here.

Applicant Specification:

• Proficiency in Python and C++

• Experience with PyTorch and other Machine Learning frameworks

• Strong understanding of computer vision fundamentals, including well-grounded knowledge of camera intrinsic and extrinsic transformations

Minimum requirements:

• Passion and enthusiasm

• Proficiency in Python and C++

• Experience with PyTorch and other Machine Learning frameworks

• Strong understanding of computer vision fundamentals, including well-grounded knowledge of camera intrinsic and extrinsic transformations

Desirable Requirements:

• Previous research experience is welcomed

• Experience with simulators such as MuJoCo, IsaacGym, Unreal Engine, or others

• Familiarity with embedded systems (FPGA, microcontrollers)

• Knowledge of orbit dynamics and orbit propagators

Process details:

• Please send your CV at contact@spaice.tech

• 8 weeks minimum fixed term contract to be agreed with successful candidate

• In-person Induction Event to be held on 24th of June 2024, and an in-person/hybrid Showcase Event.

• 5 days holiday to be taken during the placement

• Interviews will start after the application deadline

This job description set outs the skills and experience we believe are needed to be able to do this job but, research also tells us women are much more likely than men to take this list of requirements as absolute and self-select out of the process. If you think you can deliver this role then we want to hear from you, regardless of the boxes you didn’t tick.