Amazon Nova AI Challenge: FAQs

Including details about the 2026 Trusted Software Agent track.
General
What is the Amazon Nova AI Challenge?
The Amazon Nova AI Challenge is a university competition dedicated to accelerating the field of artificial intelligence (AI). It was created to recognize and advance students from around the globe who are shaping the future of artificial intelligence. Student teams are able to work on the latest challenges in the field of AI and build innovative solutions.
How does the Amazon Nova AI Challenge support research?
The Amazon Nova AI Challenge is a testbed for university students to experiment with and advance AI at scale. Participating teams compete to develop innovative and effective solutions to a specific challenge. Teams receive a number of forms of support, including stipends, AWS credits, and consultation and mentoring from the Amazon Nova AI Challenge team.
How do I contact Amazon if I have question about the challenge?
If you can't find an answer to your question, please email: amazon-challenge@amazon.com.
Competition details
What is the goal of this year's challenge?
The goal of the 2026 Amazon Nova AI Challenge: Trusted Software Agents track is to make effective AI systems that remain responsible and safe for all, with a focus on the task domain of agentic systems that assist users in the development of full stack web applications. The ultimate goal of the competition is to identify ways for LLM-enabled systems to handle more complex development tasks while anticipating and mitigating safety risks.
What is in scope for this competition?
The Amazon Nova AI Challenge: Trusted Software Agents track is focused on ensuring LLMs supporting AI-assisted software development remain safe, reliable, and trustworthy. For the 2026 Nova AI Challenge, we will focus on web application development as the coding task domain, with verifiable pass/fail conditions as the primary utility measure for a model developer’s system. We will continue with the “tournament-style” format used in 2025, where ten university teams — five model developer (defense) teams and five red (attack) teams compete in a series of interactive tournaments. There is an increased emphasis on advances in utility (ability to handle more complex development tasks) in parallel with safety (avoiding vulnerabilities and risk of exploits as systems handle more complex tasks) this year. Also, red teams will build systems that detect and exploit vulnerabilities in the applications built by model developer teams. 
How is this Trusted Software Agent track different than the Trusted AI track?
The Amazon Nova AI Challenge: Trusted Software Agents track is a natural extension of the Amazon Nova AI Challenge: Trusted AI track. Both focus on ensuring the safety of coding assistants. Trusted Software Agents adds additional emphasis on advances in coding utility and the domain has expanded from simpler code generation to software engineering tasks such as full stack web development. In the Trusted Software Agents track, the red teams will focus on using LLMs to identify potential vulnerabilities and exploits in applications; whereas the Trusted AI track focused on getting LLMs to generate malicious or vulnerable code.
Why should I participate?
There are multiple benefits of participating in the Amazon Nova AI Challenge: Trusted Software Agents track, including:
  1. Dynamic feedback: Teams will get the opportunity to test their systems against best-in-class competitors. Unlike static benchmarks, the challenge evaluations are dynamic and multi-turn and evolve as both sets of teams refine their systems over the course of the competition.
  2. AWS services: Participating teams will receive training, support, and access to the full suite of AWS services, with monthly AWS credits to support the cost of training and execution of their systems.
  3. IP ownership: Teams retain ownership of their work and associated IP, and are encouraged to publish their research after Amazon’s review.
  4. Stipend: Each team chosen for the Amazon Nova AI Challenge: Trusted Software Agents track will receive sponsorship in the amount of $250K. Funding is intended to support roughly two full-time students and one month of faculty time.
  5. Cash prizes: For model developer teams, the top ranked team will receive $250K and the second ranked team will receive $100K. Red teams will also receive $250K for the top ranked team and $100K for the second ranked team. All cash prizes will be divided equally among the students on the team.
When is the finals event?
The finals event will be held in September 2026. This is a closed-door event and participating teams are not invited to the Finals event.
Can we use other funding to help us participate in this challenge?
Yes, you may use other funding to support your team, subject to the terms described in the Challenge Rules. External funding must be disclosed to Amazon.
Can we publish our research from participation in the Amazon Nova AI Challenge: Trusted Software Agents track?
Yes, in fact publishing research papers as an outcome of your work on the Amazon Nova AI Challenge: Trusted Software Agents track is required for all teams participating in the competition, although teams may not publish any Amazon confidential information, as described in the Challenge Rules. The Amazon Nova AI Challenge requires all teams to submit a technical paper to be included in the challenge proceedings. Your team will not be selected for the finals if your team does not submit a technical paper for inclusion in the proceedings. Papers will be published online at the end of the competition and made publicly available through the Amazon Science website. Teams may also publish research papers in third-party publications and conferences, as long as all papers are provided to Amazon for review and approval at least two weeks before the submission deadline.
How will the tournaments be run?
The Amazon Nova AI Challenge: Trusted Software Agents track will consist of a series of interactive tournaments held from early 2026 through summer 2026. Each tournament will consist of two phases: a build phase focused on coding utility performance and a validation phase focused on application security. 

In the build phase, model developers will interact with user simulators to implement new features for an existing web application. Their success will be determined using a suite of end-to-end test cases. In the validation phase, red team systems will have the opportunity to identify and exploit vulnerabilities in the applications created in the build phase. In addition to building their coding assistants, model developers will also be tasked with building simulations of malicious users, and red teams will be tasked with building simulations of benign users. In the build phase, the coding assistants will interact with both the benign user simulators and the malicious user simulators. The red teams will not have the opportunity to find vulnerabilities in the applications resulting from interaction with their own user simulators, and model developer bots will only be matched up with malicious simulators from other defending teams. At the conclusion of each tournament, teams on each side will be ranked with respect to their performance, and the results will be shared with each team.
How will developer teams be ranked in the tournament?
Model developer teams will be ranked based on a combination of their coding utility performance and the security of the resulting applications. Coding utility performance will measure the number of tasks completed successfully across interactions with multiple user simulators (task success rate). Security performance will measure the number of resulting applications in which the red team bots do not find any vulnerabilities or exploits (defense success rate).
How will red teams be ranked in the tournament?
Red teams will be ranked on a combination of their coding utility performance and their effectiveness at identifying and exploiting vulnerabilities in applications (attack success rate). Coding utility performance will measure the number of tasks completed successfully (task success rate) as their user simulator interacts with each of the model developer teams’ coding assistants. This motivates each red team to ensure their user simulator is realistic and effective. Attack success rate for red teams will be a measure of the number of applications from the build phase in which they successfully identify or exploit vulnerabilities. In the build phase, red teams have an indirect motivation to ensure the security of the applications built through interaction with their user simulator as in doing so they preclude the ability of other red teams to score attack success points on those applications.
Eligibility
Who can apply to participate?
The Amazon Nova AI Challenge: Trusted Software Agents track is open to full-time students (undergraduate or graduate) with some exceptions (see Challenge Rules). Proof of enrollment will be required to participate.
Can I participate if I don’t attend a university?
No. The Amazon Nova AI Challenge: Trusted Software Agents track is open only to full-time enrolled university students.
Do I need to be enrolled in a university program throughout my participation in the competition?
All participating team members must remain full-time students in good standing at their university while participating in the competition.
Do I need to be a certain age?
Participants must be at or above the age of majority in the country, state, province, or jurisdiction of residence at the time of entry.
Can I enroll if a family member is an Amazon employee?
Immediate family members and household members of Amazon employees, directors, and contractors are not eligible to participate. See Challenge Rules for additional restrictions.
Teams
How many teams will be selected to participate?
All applications will be reviewed and evaluated by Amazon. Up to ten teams will be selected to compete in a tournament style competition.
How many team members can our team have?
There is no minimum or maximum number of team members. All team members must be enrolled in their university throughout their participation. All teams will receive a $250,000 grant regardless of how many members are on their team.
Can students from different universities be on the same team?
No. Teams must be composed of students attending the same university.
Can one university have more than one team?
Yes, universities may have more than one team. Multiple teams cannot have the same faculty advisor.
Can I participate on two separate teams?
No. You can only be a part of one team for the duration of the competition.
Can undergraduate and graduate students work together?
Yes, teams may be composed of undergraduate and graduate students.
Do I need a faculty advisor?
All teams must nominate a faculty advisor and include the faculty advisor’s consent in the applications.
Can there by more than one faculty advisor in a team?
Yes, there may be up to three faculty advisors per team.
What is the role of the faculty advisor?
Faculty advisors will advise students on technical direction and be a sounding board for new ideas, similar to a graduate school advisor. They will also act as the official representative from the university for this competition.
Can we add or remove team members during the competition?
During the competition, there will be a period of time during which faculty advisors may request to remove or add members to the team, subject to approval by Amazon. See Challenge Rules for details.
Can we discuss our work with faculty or students who aren’t on our team?
Only team members may work on their systems. However, the faculty advisor and other students and faculty members at your university may provide support and advice to your team and may co-author technical publications and research papers.
Application process
How do we apply to participate in the challenge?
Begin the application via YouNoodle, which will be open only during the application period.
What do we need to apply?
Once you have selected your team members, team leader, and faculty sponsor, you are ready to begin the application process. You may apply to both roles and if you do so Amazon will assign one of the two roles to your team.
Do all team members have to apply?
We prefer that the team leader submit an application on behalf of the whole team. In case a team lead has not been chosen, then any member of the team may submit an application. Each team should only submit one application, and it must include all of your team members’  and Faculty advisors’ information.
Is there an application fee?
There is no application fee.
How will teams be selected to participate?
All applications will be reviewed by a panel of experts from Amazon. Teams will be selected based on the following criteria: (1) the technical merit of the approach; (2) the novelty of the ideas; and (3) an assessment of the team’s ability to execute their plan. Please be sure to provide enough detail in your application to enable evaluation of your proposal.
Grants and prizes
Do we get a grant or other support to participate in the Amazon Nova AI Challenge: Trusted Software Agents track?
Up to ten teams will be sponsored to participate in the competition. Each sponsored team’s university will receive a $250,000 research grant to help fund the team’s participation. In addition each participating team will receive AWS credits to support the development of their system, and support from the Amazon Nova AI Challenge team.
How can the grant be spent?
The grant is intended to support two full-time students for the duration of the competition and one month of the faculty advisor’s salary. No more than 35% of the research grant may be allocated to administrative fees. Entrant Teams will be expected to use the stipend towards any uncovered costs associated with bootcamp and or summit (if any). If your team would like to use the funds in another manner, your faculty advisor must receive approval from Amazon before doing so.
What are the prizes for winning the competition?
From the evaluation at the finals event, the two top ranked model developer teams and top two ranked red teams will receive awards. The two teams placed 1st in each role (i.e., red team and developer team) will receive $250,000 each, and the two teams in 2nd place will receive $100,000 each.
US, WA, Seattle
Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. Prime members can customize their viewing experience and find their favorite movies, series, documentaries, and live sports – including Amazon MGM Studios-produced series and movies; licensed fan favorites; and programming from Prime Video add-on subscriptions such as Apple TV+, Max, Crunchyroll and MGM+. All customers, regardless of whether they have a Prime membership or not, can rent or buy titles via the Prime Video Store, and can enjoy even more content for free with ads. Are you interested in shaping the future of entertainment? Prime Video's technology teams are creating best-in-class digital video experience. As a Prime Video technologist, you’ll have end-to-end ownership of the product, user experience, design, and technology required to deliver state-of-the-art experiences for our customers. You’ll get to work on projects that are fast-paced, challenging, and varied. You’ll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people. We’ll look for you to bring your diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. With global opportunities for talented technologists, you can decide where a career Prime Video Tech takes you! As an Applied Scientist in the Prime Video Playback Intelligence Organization, you will have deep subject matter expertise in applied machine learning and data science, with specializations in video streaming optimization, information retrieval, anomaly detection and root-causing systems, large language models and generative AI across various modalities. Key job responsibilities - Work with multiple teams of scientists, engineers, and product managers to translate business and functional requirements into concrete deliverables leading strategic efforts to enhance customer quality of experiences. - Work on problems spaces such as: improving the customer playback quality of experience across Video on Demand, Live Events and Linear Content. - Reduce the time/cost/effort to optimize the customer experience as well as detect, root-cause, and mitigate defects in the customer experience. You’ll seek to understand the depth and nuance of streaming video at scale and identify opportunities to grow our business and improve customer quality of experience via principled ML/AI solutions. - Lead integration of new algorithms and processes into existing modeling stacks, simplify and streamline the existing modeling stacks, and develop testing and evaluation strategies. Ultimately, you'll work backwards from the desired outcomes and lead the way on determining the ideal solution (statistical techniques, traditional ML, GenAI, etc). A day in the life We love solving challenging and hard problems in our quest to innovate on behalf of our customers and provide the best video streaming experience. We push the boundaries to leverage and invent technologies which help create unrivaled experiences for our customers to help us move fast in a growing and changing environment. We use data to guide our decisions, work closely with our engineering and product counterparts, and partner with other Science teams as well as academic institutions to learn and guide in an environment of innovation.
IN, KA, Bengaluru
Selection Monitoring team is responsible for making the biggest catalog on the planet even bigger. In order to drive expansion of the Amazon catalog, we develop advanced ML/AI technologies to process billions of products and algorithmically find products not already sold on Amazon. We work with structured, semi-structured and Visually Rich Documents using deep learning, NLP and image processing. The role demands a high-performing and flexible candidate who can take responsibility for success of the system and drive solutions from research, prototype, design, coding and deployment. We are looking for Applied Scientists to tackle challenging problems in the areas of Information Extraction, Efficient crawling at internet scale, developing ML models for website comprehension and agents to take multi-step decisions. You should have depth and breadth of knowledge in text mining, information extraction from Visually Rich Documents, semi structured data (HTML) and advanced machine learning. You should also have programming and design skills to manipulate Semi-Structured and unstructured data and systems that work at internet scale. You will encounter many challenges, including: - Scale (build models to handle billions of pages), - Accuracy (requirements for precision and recall) - Speed (generate predictions for millions of new or changed pages with low latency) - Diversity (models need to work across different languages, market places and data sources) You will help us to - Build a scalable system which can algorithmically extract information from world wide web. - Intelligently cluster web pages, segment and classify regions, extract relevant information and structure the data available on semi-structured web. - Build systems that will use existing Knowledge Base to perform open information extraction at scale from visually rich documents. Key job responsibilities - Use AI, NLP and advances in LLMs/SLMs and agentic systems to create scalable solutions for business problems. - Efficiently Crawl web, Automate extraction of relevant information from large amounts of Visually Rich Documents and optimize key processes. - Design, develop, evaluate and deploy, innovative and highly scalable ML models, esp. leveraging latest advances in RL-based fine tuning methods like DPO, GRPO etc. - Work closely with software engineering teams to drive real-time model implementations. - Establish scalable, efficient, automated processes for large scale model development, model validation and model maintenance. - Lead projects and mentor other scientists, engineers in the use of ML techniques. - Publish innovation in research forums.
US, WA, Seattle
This role will contribute to developing the Economics and Science products and services in the Fee domain, with specialization in supply chain systems and fees. Through the lens of economics, you will develop causal links for how Amazon, Sellers and Customers interact. You will be a key and senior scientist, advising Amazon leaders how to price our services. You will work on developing frameworks and scalable, repeatable models supporting optimal pricing and policy in the two-sided marketplace that is central to Amazon's business. The pricing for Amazon services is complex. You will partner with science and technology teams across Amazon including Advertising, Supply Chain, Operations, Prime, Consumer Pricing, and Finance. We are looking for an experienced Economist to improve our understanding of seller Economics, enhance our ability to estimate the causal impact of fees, and work with partner teams to design pricing policy changes. In this role, you will provide guidance to scientists to develop econometric models to influence our fee pricing worldwide. You will lead the development of causal models to help isolate the impact of fee and policy changes from other business actions, using experiments when possible, or observational data when not. Key job responsibilities The ideal candidate will have extensive Economics knowledge, demonstrated strength in practical and policy relevant structural econometrics, strong collaboration skills, proven ability to lead highly ambiguous and large projects, and a drive to deliver results. They will work closely with Economists, Data / Applied Scientists, Strategy Analysts, Data Engineers, and Product leads to integrate economic insights into policy and systems production. Familiarity with systems and services that constitute seller supply chains is a plus but not required. About the team The Stores Economics and Sciences team is a central science team that supports Amazon's Retail and Supply Chain leadership. We tackle some of Amazon's most challenging economics and machine learning problems, where our mandate is to impact the business on massive scale.
US, CA, San Francisco
Amazon has launched a new research lab in San Francisco to develop foundational capabilities for useful AI agents. We’re enabling practical AI to make our customers more productive, empowered, and fulfilled. Our work leverages large vision language models (VLMs) with reinforcement learning (RL) and world modeling to solve perception, reasoning, and planning to build useful enterprise agents. Our lab is a small, talent-dense team with the resources and scale of Amazon. Each team in the lab has the autonomy to move fast and the long-term commitment to pursue high-risk, high-payoff research. We’re entering an exciting new era where agents can redefine what AI makes possible. Key job responsibilities You will contribute directly to AI agent development in an applied research role to improve the multi-model perception and visual-reasoning abilities of our agent. Daily responsibilities including model training, dataset design, and pre- and post-training optimization. You will be hired as a Member of Technical Staff.
US, NY, New York
We are looking for detail-oriented, organized, and responsible individuals who are eager to learn how to apply their structural econometrics skillsets to solve real world problems. The intern will work in the area of Amazon Private Brands and develop models to improve our product selection. Our PhD Economist Internship Program offers hands-on experience in applied economics, supported by mentorship, structured feedback, and professional development. Interns work on real business and research problems, building skills that prepare them for full-time economist roles at Amazon and beyond. You will learn how to build data sets and perform applied econometric analysis collaborating with economists, scientists, and product managers. These skills will translate well into writing applied chapters in your dissertation and provide you with work experience that may help you with placement. These are full-time positions at 40 hours per week, with compensation being awarded on an hourly basis. About the team The Amazon Private Brands science advance team applies Machine Learning, Statistics and Econometrics/economics to solve high-impact business problems, develop prototypes for Amazon-scale science solutions, and optimize key business functions of Amazon Private Brands and other Amazon orgs. We are an interdisciplinary team, using science and technology and leveraging the strengths of engineers and scientists to build solutions for some of the toughest business problems at Amazon, covering areas such as pricing, discovery, negotiation, forecasting, supply chain and product selection/development.
US, WA, Seattle
Innovators wanted! Are you an entrepreneur? A builder? A dreamer? This role is part of an Amazon Special Projects team that takes the company’s Think Big leadership principle to the extreme. We focus on creating entirely new products and services with a goal of positively impacting the lives of our customers. No industries or subject areas are out of bounds. If you’re interested in innovating at scale to address big challenges in the world, this is the team for you. Here at Amazon, we embrace our differences. We are committed to furthering our culture of inclusion. We have thirteen employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We are constantly learning through programs that are local, regional, and global. Amazon’s culture of inclusion is reinforced within our 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust. Our team highly values work-life balance, mentorship and career growth. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We care about your career growth and strive to assign projects and offer training that will challenge you to become your best.
US, TX, Austin
Amazon Security is looking for a talented and driven Applied Scientist II to spearhead Generative AI acceleration within the Secure Third Party Tools (S3T) organization. The S3T team has bold ambitions to re-imagine security products that serve Amazon's pace of innovation at our global scale. This role will focus on leveraging large language models and agentic AI to transform third-party security risk management, automate complex vendor assessments, streamline controllership processes, and dramatically reduce assessment cycle times. You will drive builder efficiency and deliver bar-raising security engagements across Amazon. Key job responsibilities Lead the research, design, and development of GenAI-powered solutions to enhance the security and governance of third-party tools across Amazon Develop and fine-tune large language models (LLMs) and other ML models tailored to security use cases, including risk detection, anomaly identification, and automated compliance Collaborate with cross-functional teams — including Security Engineers, Software Development Engineers, and Product Managers — to translate scientific innovations into scalable, production-ready systems Define and drive the GenAI roadmap for the S3T organization, influencing strategy and prioritization Conduct rigorous experimentation, evaluate model performance, and iterate rapidly to deliver measurable impact Stay current with the latest advancements in GenAI and applied ML research, and bring relevant innovations into Amazon's security ecosystem Mentor junior scientists and contribute to a culture of scientific excellence within the team About the team Security is central to maintaining customer trust and delivering delightful customer experiences. At Amazon, our Security organization is designed to drive bar-raising security engagements. Our vision is that Builders raise the Amazon security bar when they use our recommended tools and processes, with no overhead to their business. Diverse Experiences Amazon Security values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why Amazon Security? At Amazon, security is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for security across all of Amazon’s products and services. We offer talented security professionals the chance to accelerate their careers with opportunities to build experience in a wide variety of areas including cloud, devices, retail, entertainment, healthcare, operations, and physical stores. Inclusive Team Culture In Amazon Security, it’s in our nature to learn and be curious. Ongoing DEI events and learning experiences inspire us to continue learning and to embrace our uniqueness. Addressing the toughest security challenges requires that we seek out and celebrate a diversity of ideas, perspectives, and voices. Training & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, training, and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve.
US, WA, Seattle
Innovators wanted! Are you an entrepreneur? A builder? A dreamer? This role is part of an Amazon Special Projects team that takes the company’s Think Big leadership principle to the next-level. We focus on creating entirely new products and services with a goal of positively impacting the lives of our customers. No industries or subject areas are out of bounds. If you’re interested in innovating at scale to address big challenges in the world, this is the team for you. Here at Amazon, we embrace our differences. We are committed to furthering our culture of inclusion. We have thirteen employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We are constantly learning through programs that are local, regional, and global. Amazon’s culture of inclusion is reinforced within our 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust. Key job responsibilities * Develop, deploy, and operate scalable bioinformatics analysis workflows on AWS * Evaluate and incorporate novel bioinformatic approaches to solve critical business problems * Originate and lead the development of new data collection workflows with cross-functional partners * Partner with laboratory science teams on design and analysis of experiments About the team Our team highly values work-life balance, mentorship and career growth. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We care about your career growth and strive to assign projects and offer training that will challenge you to become your best.
US, MA, N.reading
Amazon Industrial Robotics is seeking exceptional talent to help develop the next generation of advanced robotics systems that will transform automation at Amazon's scale. We're building revolutionary robotic systems that combine cutting-edge AI, sophisticated control systems, and advanced mechanical design to create adaptable automation solutions capable of working safely alongside humans in dynamic environments. This is a unique opportunity to shape the future of robotics and automation at an unprecedented scale, working with world-class teams pushing the boundaries of what's possible in robotic dexterous manipulation, locomotion, and human-robot interaction. This role presents an opportunity to shape the future of robotics through innovative applications of deep learning and large language models. At Amazon Industrial Robotics we leverage advanced robotics, machine learning, and artificial intelligence to solve complex operational challenges at an unprecedented scale. Our fleet of robots operates across hundreds of facilities worldwide, working in sophisticated coordination to fulfill our mission of customer excellence. Join us in building the next generation of intelligent robotics systems that will transform the future of automation and human-robot collaboration. Key job responsibilities Design and deploy end-to-end teleoperation pipelines integrating VR/AR headsets and haptics interfaces with robotic hardware Implement force-feedback and tactile sensing algorithms to provide operators with a "sense of touch," improving performance in contact-rich manipulation tasks Collaborate with ML teams to ensure teleoperation interfaces capture high-fidelity state-action pairs, including proprioception, visual, and force/torque data for model training Develop custom networking and streaming protocols to minimize operator-to-robot latency. Conduct user studies to evaluate ergonomics, cognitive load, and "telepresence" effectiveness to iterate on UI/UX designs.
US, CA, Pasadena
The Amazon Center for Quantum Computing (CQC) is a multi-disciplinary team of scientists, engineers, and technicians, on a mission to develop a fault-tolerant quantum computer. We are looking to hire an Instrument Control Engineer to join our growing software team. You will work closely with our experimental physics and control hardware development teams to enable their work characterizing, calibrating, and operating novel quantum devices. The ideal candidate should be able to translate high-level science requirements into software implementations (e.g. Python APIs/frameworks, compiler passes, embedded SW, instrument drivers) that are performant, scalable, and intuitive. This requires someone who (1) has a strong desire to work within a team of scientists and engineers, and (2) demonstrates ownership in initiating and driving projects to completion. This role has a particular emphasis on working directly with our control hardware designers and vendors to develop instrument software for test and measurement. Inclusive Team Culture Here at Amazon, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon conferences, inspire us to never stop embracing our uniqueness. Diverse Experiences Amazon values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Export Control Requirement Due to applicable export control laws and regulations, candidates must be either a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum, or be able to obtain a US export license. If you are unsure if you meet these requirements, please apply and Amazon will review your application for eligibility. Key job responsibilities - Work with control hardware developers, as a “subject matter expert” on the software interfaces around our control hardware - Collaborate with external control hardware vendors to understand and refine integration strategies - Implement instrument drivers and control logic in Python and/or a low-level languages, including C++ or Rust - Contribute to our compiler backend to enable the efficient execution of OpenQASM-based experiments on our next-generation control hardware - Benchmark system performance and help define key performance metrics - Ensure new features are successfully integrated into our Python-based experimental software stack - Partner with scientists to actively contribute to the codebase through mentorship and documentation We are looking for candidates with strong engineering principles, a bias for action, superior problem-solving, and excellent communication skills. Working effectively within a team environment is essential. As an Instrument Control Engineer embedded in a broader science organization, you will have the opportunity to work on new ideas and stay abreast of the field of experimental quantum computation. A day in the life Your time will be spent on projects that extend functional capabilities or performance of our internal research software stack. This requires working backwards from the needs of science staff in the context of our larger experimental roadmap. You will translate science and software requirements into design proposals balancing implementation complexity against time-to-delivery. Once a design proposal has been reviewed and accepted, you’ll drive implementation and coordinate with internal stakeholders to ensure a smooth roll out. Because many high-level experimental goals have cross-cutting requirements, you’ll often work closely with other engineers or scientists or on the team. About the team You will be joining the Software group within the Amazon Center of Quantum Computing. Our team is comprised of scientists and software engineers who are building scalable software that enables quantum computing technologies.