Staff Engineer, Reinforcement Learning (R3639) at Shield AI

California, United States

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Defense, AerospaceIndustries

Requirements

Master's degree in Computer Science, Robotics, or a related field and 5+ years of relevant professional experience or PhD with 4+ years of relevant experience
Professional C++ production deployment skills (primary experience in Python is unlikely to be a good fit; familiarity with Python prototyping is welcome)
Demonstrated experience deploying reinforcement learning algorithms in production environments
Strong background deploying RL algorithms in production following full Software development lifecycle
Ability to independently deploy high-reliability code suitable for real-world autonomous systems
Experience with RL frameworks (e.g., TensorFlow (C++), libtorch, etc.) and RL training environments (e.g., OpenAI Gymnasium, Google DeepMind Control Suite, etc.)
Solid understanding of software engineering best practices, including version control, testing, and CI/CD
Familiarity with CUDA
Excellent problem-solving skills

Responsibilities

Design, implement, and deploy reinforcement learning algorithms for a variety of platforms
Collaborate with teams across the organization to integrate RL solutions that meet customer specifications
Analyze and optimize performance of deployed RL models in dynamic environments
Develop tools and infrastructure to support large-scale training, simulation, and evaluation
Mentor and provide technical guidance to junior engineers
Stay current with the latest advancements in RL, and apply them to solve challenging problems
Contribute to the design and architecture of scalable, maintainable software systems
Leverage expertise in robotics and Reinforcement Learning (RL) to develop, deploy, and optimize models for autonomous systems
Collaborate with cross-functional teams to deliver robust, scalable solutions that advance the state of Hivemind SDK
Contribute to developing technical requirements, test plans, and validating the performance of algorithms and models

Skills

Key technologies and capabilities for this role

Reinforcement LearningRoboticsMotion PlanningBehavior PlanningAutonomous SystemsAlgorithm DevelopmentModel DeploymentModel OptimizationReal-world Testing

Questions & Answers

Common questions about this position

What is the salary range for this Staff Engineer position?

This information is not specified in the job description.

Is this role remote or does it require working from an office?

This information is not specified in the job description.

What qualifications and skills are required for this role?

A Master's degree in Computer is required. Expertise in robotics and Reinforcement Learning (RL) is essential, along with the ability to design, implement, deploy RL algorithms, optimize models, and contribute to scalable software systems.

What is the team culture like at Shield AI?

The Hivemind Pilot team is an agile group of engineers focused on building state-of-the-art autonomy software, with the Behavior and Motion Planning team developing and rigorously testing algorithms for reliable real-world performance. The company emphasizes collaboration with cross-functional teams to deliver robust solutions.

What makes a strong candidate for this Staff Engineer role?

Strong candidates will have a Master's degree, expertise in robotics and RL, experience designing and deploying RL algorithms, ability to optimize models in dynamic environments, and skills in mentoring junior engineers while staying current with RL advancements.

Shield AI

Develops AI and autonomous systems for defense

About Shield AI

Shield AI specializes in creating artificial intelligence and autonomous systems specifically for the defense industry. The company develops AI-powered systems, including autonomous drones, that assist military operations, especially in environments where GPS and communication may not be available. This technology allows for safer and more efficient defense operations. Shield AI differentiates itself from competitors by focusing on advanced AI capabilities and securing significant contracts with government and military clients, such as the multi-billion dollar EWAAC contract. The company's goal is to enhance operational capabilities and safety in military contexts, ultimately aiming to protect lives through its innovative solutions.

San Diego, CaliforniaHeadquarters

2015Year Founded

$772.8MTotal Funding

DEBTCompany Stage

AI & Machine Learning, DefenseIndustries

501-1,000Employees

Benefits

Medical Insurance Coverage

Long Term Disability Insurance

Health Care FSA and Dependent Care FSA

Employee Assistance Program

Subsidized Gym Membership

Pet Insurance

Competitive Compensation

Retirement Services

Life Insurance

Parental Leave

Bereavement Support

Flexible Work Hours

PTO

Paid Holidays

Commuter Benefits

Relaxed Dress Code

Yearly Swag Items

Unlimited Snacks

Bottomless Beverages

Annual Celebrations

Work From Home Benefits

Standing Desks and Widescreen Monitors

Risks

Increased competition from companies like Waymo could divert investment from Shield AI.

Geopolitical tensions may challenge the JSW Defence partnership for V-BAT production in India.

Dependency on Palantir's infrastructure may limit Shield AI's operational flexibility.

Differentiation

Shield AI's Hivemind is the first autonomous AI pilot deployed in combat since 2018.

Strategic partnerships with Palantir and JSW Defence enhance technological capabilities and market reach.

Shield AI's V-BAT drone is selected for a $198 million U.S. Coast Guard contract.

Upsides

Increased demand for autonomous systems in defense boosts Shield AI's market potential.

Successful multi-aircraft autonomous flight tests showcase advanced AI piloting capabilities.

Significant investment in robotics indicates a robust market for Shield AI's offerings.

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