Senior Machine Learning Engineer II

Senior Machine Learning Engineer II

Long Beach, CA

Rocket Lab is the end-to-end space company building rockets, spacecraft, and critical subsystems that keep the world connected, protected, expand humanity's reach to the Moon, Mars, and beyond. We move fast, build real hardware for meaningful missions, and make the impossible routine. Come shape the future with us.

At Rocket Lab, we're not just launching rockets — we're building the future of space. Our Space Systems team builds everything from complete spacecraft, precision payloads to the components and subsystems that allow them to thrive in space, like solar panels, flight software, star trackers, optical systems, separation systems, radios, and more.

Our Space Systems team has enabled more than 1,700 missions, ranging from interplanetary exploration, in-space manufacturing to national security and defense initiatives. The team has built spacecraft, payloads, and components for missions to the Moon and Mars, working with partners including NASA, the Space Development Agency, and the U.S. Space Force. Whether it's a single high-performance spacecraft, constellation, or the vertically integrated components that help them get to space — our world class Space Systems team is empowering some of the boldest and most ambitious space missions.

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, Optical Systems delivers solutions to the warfighter for responsive, scalable sensing solutions across all orbital domains.

As a Senior Machine Learning Engineer II based at our Optical Systems sites in Long Beach, CA, you will have the opportunity to support Tranche 3 of the U.S. Space Development Agency's (SDA) Proliferated Warfighter Space Architecture (PWSA) and beyond by building deep learning neural networks for advanced Electro-Optical (EO/IR) image processing.

What You'll Do

• Contribute your experience to developing solutions for real-world problems.
• Design, train, and deploy machine learning models for Optical Systems applications
• Build and maintain ML pipelines for data ingestion, feature engineering, training, and inference.
• Collaborate with other researchers/engineers on artificial intelligence, machine learning, and computer vision.
• Perform rapid prototyping and enhanced development to be integrated into operational systems.
• Perform troubleshooting, bug fixes, and maintenance of existing and new systems.
• Stay current with ML research and evaluate new tools, frameworks, and techniques

What We're Looking For In A Senior Machine Learning Engineer II:

• Bachelor's degree and 8+ years of experience, master's degree and 6+ years of experience, or a Ph.D. in Computer Science, Electrical and Computer Engineering, Mechanical Engineering, Physics, or related field
• Strong background in machine learning including model selection, architecting, training, validation, testing, and deployment
• Experience in building deep learning neural network for computer vision, image processing, or video analysis (e.g., object detection, image segmentation, and tracking)
• Strong math background, particularly linear algebra
• Proficiency in Python
• Experience with deep learning libraries (Keras, TensorFlow, Pytorch, etc)
• Software engineering fundamentals: version control, testing, CI/CD, containerization
• U.S. citizenship is required, due to program requirements
• Ability to obtain and maintain an U.S. Government Security Clearance

Nice To Have:

• Proficiency in C/C++/Rust
• Experience curating quality, real-world datasets for training deep learning models
• TS/SCI security clearance

This position may require prolonged periods of sitting, standing, walking, computer work, and occasional exposure to moderate levels of noise, dust, and fumes in production areas.

Join one of the world's fastest-growing space companies and own a piece of it. In addition to competitive base pay, you'll receive company stock as part of your total compensation package, giving you a direct stake in our success. As we expand to new launch sites, groundbreaking missions, and global markets, your ownership has the opportunity to grow alongside the company. Our comprehensive benefits package includes our industry-leading Employee Stock Purchase Program (with a 15% discount on company stock), top-tier medical plans (HMO, PPO, and a zero cost HDHP option with a significant HSA company contribution), dental and vision coverage, paid vacation and sick time, 11 paid holidays, flexible spending and dependent care accounts, paid parental leave, disability and life insurance, and a 401(k) retirement plan with company match. Additional perks include subsidized EV charging, onsite fitness centers (where available), discounted gym memberships, complimentary snacks and beverages, 50% employee discount on our popular merch store, and a variety of other employee discounts. Level and base salary will be determined on a case-by-case basis and may vary based on the following considerations: job-related knowledge and skills, education, and experience.

Base Pay Range (CA Only)

$153,000 - $229,500 USD

What To Expect

We're on a mission to unlock the potential of space to improve life on Earth, but that's not an easy task. It takes hard work, determination, relentless innovation, teamwork, grit, and an unwavering commitment to achieving what others often deem impossible. Our people out-think, out-work, and out-pace. We pride ourselves on having each other's backs, checking our egos at the door, and rolling up our sleeves on all tasks big and small. We thrive under pressure, work to tight deadlines, and our focus is always on how we can deliver, rather than dwelling on the challenges that stand in the way.