At SandboxAQ, we are committed to competitive, equitable, and transparent compensation; we continuously benchmark our salaries and total compensation to premium markets to ensure our competitiveness. Individual pay within the above range is determined by job-related skills, experience, education, and geographic location.

With a focus on pay equity and ensuring opportunity for future salary progression, our typical practice is to hire within the first half of the base salary range for a given role and level. This approach allows us to reward performance and increasing expertise consistently as your career develops with us.

We use two geographic pay tiers to reflect the pay differences in local markets:

• Tier 1: Applies to candidates located within 75 miles of San Francisco, Los Angeles, Seattle, New York, Boston, and Washington, DC.

• Tier 2: Applies to candidates located in all other Locations in the US.

About SandboxAQ

SandboxAQ is a high-growth company delivering AI solutions that address some of the world's greatest challenges. The company’s Large Quantitative Models (LQMs) power advances in life sciences, financial services, navigation, cybersecurity, and other sectors.

We are a global team that is tech-focused and includes experts in AI, chemistry, cybersecurity, physics, mathematics, medicine, engineering, and other specialties. The company emerged from Alphabet Inc. as an independent, growth capital-backed company in 2022, funded by leading investors and supported by a braintrust of industry leaders.

At SandboxAQ, we’ve cultivated an environment that encourages creativity, collaboration, and impact. By investing deeply in our people, we’re building a thriving, global workforce poised to tackle the world's epic challenges. Join us to advance your career in pursuit of an inspiring mission, in a community of like-minded people who value entrepreneurialism, ownership, and transformative impact.

The Opportunity

SandboxAQ’s AI/Quantum Navigation (“AQNav”) team is looking for their next R&D Intern! In this internship, you will help design and run sensor characterization experiments that span hardware test setups, controlled measurements, and data collection across multiple candidate sensors. You will analyze the resulting data to extract key performance parameters and uncertainties, then incorporate those parameters into navigation simulations to quantify how sensor choices affect end-to-end system accuracy. You will compare candidate sensors across realistic mission scenarios, highlight performance and risk trade-offs, and help translate those findings into clear recommendations for our sensor and navigation roadmaps, including cost and supply-chain considerations where relevant. Embedded within the Hardware team, you will collaborate closely with our Data/ML and Navigation teams to iterate on test plans, modeling approaches, and decision criteria as new data and constraints emerge.

Key Responsibilities

• Conduct hands-on characterization measurements of candidate sensors, designing and executing experiments to capture key performance parameters (e.g., noise, stability, linearity, bandwidth).

• Analyze experimental data rigorously using statistical and signal-processing techniques to quantify sensor performance and uncertainty.

• Integrate characterized sensor parameters into navigation simulations to assess their impact on overall system performance and accuracy across representative mission scenarios.

• Develop comparative performance models and visualizations that clearly highlight trade-offs between different sensor options (e.g., accuracy vs. cost vs. robustness).

• Produce a comprehensive sensor performance trade report that ties sensor-level metrics to system-level navigation outcomes and provides clear, data-driven recommendations.

• Where appropriate, incorporate cost and supply-chain considerations into your analysis to strengthen the overall business case for sensor selection.

• Collaborate closely with the hardware, data, and navigation teams.

• Present findings and recommendations to product leadership, iterating on the study design as new data, constraints, or opportunities emerge.

Essential Skills & Experience

• Currently enrolled in, or recently graduated from, an undergraduate or graduate program in Electrical Engineering, Physics, or a closely related field.

• Hands-on experience working with physical sensors (e.g., inertial, magnetic, or related), including data collection, basic calibration, and noise/performance characterization.

• Demonstrated proficiency in quantitative data analysis using tools such as Python, MATLAB, or similar, including statistical analysis and visualization of experimental results.

• Strong writing and communication skills, with prior experience writing or presenting technical reports or project deliverables that synthesize data, methods, and conclusions.

• Ability to work both independently and collaboratively in a multidisciplinary environment.

Highly Desired Skills & Experience

• Experience designing and executing sensor test campaigns, including test planning, instrumentation, and experimental design.

• Prior internships, co-ops, or lab experience in an R&D, hardware, or systems engineering setting.

Other Details

• This is a time-bound residency position; ideally for Summer 2026

• This role is a hybrid internship with recurring on-site work in Palo Alto, CA for testing and collaboration.

SandboxAQ Welcomes All

We are committed to fostering a culture of belonging and respect, where diverse perspectives are actively sought and valued. Our multidisciplinary environment provides ample opportunity for continuous growth - working alongside humble, empowered, and ambitious colleagues ready to tackle epic challenges.

Equal Employment Opportunity: All qualified applicants will receive consideration regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status.

Accommodations: We provide reasonable accommodations for individuals with disabilities in job application procedures for open roles. If you need such an accommodation, please let a member of our Recruiting team know.

Read: Guidance for candidates on using AI Tools in interviews

Compensation Range: $56K - $84K