Senior Machine Learning Engineer I

Senior Machine Learning Engineer I

Rocket Lab is an end-to-end space company delivering responsive launch services, complete spacecraft design and manufacturing, payloads, satellite components, and more – all with the goal of opening access space. The rockets and satellites we build, and launch enable some of the most ambitious and vital space missions globally, supporting scientific exploration, Earth observation and missions to combat climate change, national security, and exciting new technology demonstrations.

Our Electron rocket has become the second most frequently launched U.S. rocket annually and has delivered more than 230 satellites to orbit, all while we work to develop Neutron, our upcoming medium-lift, reusable launch vehicle for larger constellation deployment. Our Space Systems business designs and builds our extensive line of satellites, payloads, and their components, including spacecraft that have been selected to support NASA missions to the Moon and Mars and components used on the James Webb Space Telescope.

Rocket Lab's Optical Systems division solves mission-critical space domain and Intelligence, Surveillance, and Reconnaissance (ISR) challenges for Department of Defense (DoD) and Intelligence Community (IC) customers. Our vision is to revolutionize the space-based payload market with innovative and novel designs for space, terrestrial, and airborne environments. Building on more than 20 years of electro-optical and infrared systems innovation from Geost, Optical Systems delivers solutions to the warfighter for responsive, scalable sensing solutions across all orbital domains.

As a Senior Machine Learning Engineer I based at our Optical Systems site in Tucson, AZ, you will have the opportunity to collaborate with researchers on high-impact ML, AI, and computer vision projects. Join a driven team of pioneers relentlessly tackling challenging projects, delivering on the impossible, and making an impact on the future of space!

What you'll get to do:

• Collaborate with researchers on projects related to machine learning, artificial intelligence, and computer vision
• Perform rapid prototyping and enhanced development to be integrated into operational systems
• Contribute your strong programming ability and experience to develop robust solutions for real-world problems
• Validate, optimize, and deploy advanced exploitation algorithms
• Perform troubleshooting, bug fixes, and maintenance of existing and new code to ensure stability and robustness.
• Perform other duties as assigned
• Ability to support travel or off-site work, as needed

You'll bring these qualifications:

• Bachelor's degree in computer science, electrical or computer engineering, mechanical engineering, physics, or other field
• 5+ years of software experience
• Active TS/SCI U.S. Government Security Clearance
• Proficiency in Python
• Experience with deep learning libraries (PyTorch, TensorFlow, etc.)
• Strong background in both classical and modern (deep learning) machine learning including model selection, architecting, training, validation, testing, and deployment
• Understanding of a variety of machine learning tasks, e.g. Object Detection, Segmentation, Re-Identification, Tracking, Super Resolution
• Ability to apply modern AI approaches to solve real-world problems

These qualifications would be nice to have:

• Machine learning experience with imagery or 3-D data
• Master's degree or PhD in computer science, electrical or computer engineering, mechanical engineering, physics, or other science or engineering field
• Classical machine learning methods
• Experience with AWS, docker, Agile development
• Experience curating quality, real-world datasets for training deep learning models
• Proficiency in C++, MATLAB

Additional requirements:

• Specific vision abilities required by this job include close vision, distance vision, peripheral vision, depth perception, and the ability to focus
• Regularly required to sit, use hands and fingers, operate computer keyboard and controls, and communicate verbally and in writing
• Must be physically able to commute to buildings
• Occasional exposure to dust, fumes and moderate levels of noise