The ideal candidate possesses deep expertise in classical optimization algorithms, robust Python programming skills, and a solid foundation in data modeling. Experience with developing hybrid quantum optimization solutions is a plus.

You will leverage state-of-the-art, GenAI-powered development tools such as Claude Code to accelerate solution development and enhance our optimization software. This role demands creative problem-solving, a self-starter mentality, and the ability to rapidly apply algorithmic theory and mathematic modeling to practical, real-world optimization challenges.

You will be designing, implementing, and deploying optimization algorithms and services that integrate seamlessly into larger defense systems, working across various platforms (on-prem, cloud, and hybrid quantum computing environments).

Familiarity with modeling linear and non-linear optimization problems, rapid prototyping, integrating optimization solutions into existing architectures, leveraging APIs, and utilizing open-source tools will be crucial.

If you thrive in a dynamic environment that values creative problem-solving, love writing code, excel as both an individual contributor and team player, are eager to learn, and bring a can-do attitude, this role is for you.

Key Responsibilities:

• Design, develop, and implement highly efficient optimization algorithms and software solutions to solve challenging problems in areas such as resource allocation, scheduling, routing, mission planning, control systems, and supply chain logistics.

• Apply classical optimization techniques (e.g., linear programming, mixed-integer linear programming, combinatorial optimization, network flow, dynamic programming, heuristics, metaheuristics) to model and explore novel approaches.

• Utilize GenAI tools (e.g., OpenAI Codes, Claude Code, GitHub Copilot) to rapidly prototype, refine, and test algorithmic solutions, improving development velocity and code quality.

• Develop robust data models and efficient data pipelines to support complex optimization problems, ensuring data integrity and efficient processing for algorithmic inputs and outputs.

• Collaborate with multidisciplinary teams (software engineers, data scientists, domain experts, product managers) to integrate optimization engines and services into larger defense systems and platforms.

• Perform rigorous testing, validation, and performance analysis of optimization solutions, ensuring scalability, reliability, and accuracy under diverse operational conditions.

• Participate actively in the entire Software Development Lifecycle (SDLC) from requirements gathering and design to deployment, monitoring, and maintenance.

• Support Anduril- and customer-funded R&D efforts, contributing to technical documentation, presentations, and patent applications.

Requirements:

• Bachelor's degree in Computer Science, Software Engineering, Applied Mathematics, Operations Research, or a related quantitative field.

• 3+ years of professional experience in software development with a dedicated focus on optimization, algorithmic problem-solving, or operations research.

• Experience solving optimization problems in defense, transportation, supply chain, logistics, network optimization, smart grids or similar.

• Expert proficiency in Python for scientific computing and robust software development.

• Strong theoretical and practical understanding of classical optimization algorithms (e.g., linear programming, mixed-integer linear programming, constraint programming, network flow, dynamic programming, heuristics, meta heuristics).

• Hands-on experience with optimization libraries and commercial/open-source solvers (e.g., SciPy Optimize, PuLP, CVXPY, Gurobi, CPLEX, OR-Tools, GEKKO).

• Solid experience with data modeling, data structures, and algorithms to efficiently prepare, process, and manage data for optimization problems.

• Demonstrable hands-on experience using GenAI tools (e.g., OpenAI Codex, Claude Code, Gemini Code Assist, GitHub Copilot, Amazon CodeWhisperer, or similar) for software development, code generation, debugging, and algorithmic exploration.

• Proficiency in using numerical computing libraries such as NumPy, SciPy, and Pandas.

• Demonstrated understanding and application of software testing principles and practices, including unit testing, integration testing, and end-to-end testing.

• Ability to develop, test, and deploy software effectively on Linux-based systems.

• Eligible to obtain and maintain an active U.S. Top Secret SCI security clearance.

• Experience with Git version control, build tools, and CI/CD pipelines.

• Strong problem-solving skills, meticulous attention to detail, and the ability to work effectively in a collaborative team environment.

• Excellent communication and interpersonal skills, with the ability to effectively articulate complex technical concepts to diverse audiences.

Preferred Qualifications:

• Master's or Ph.D. in Computer Science, Applied Mathematics, Operations Research, or a closely related quantitative field.

• Familiarity with or a strong interest in quantum optimization algorithms, quantum computing concepts, or quantum-inspired heuristic approaches.

• Experience with D-Wave’s quantum annealing platform is a plus.

• Experience with performance-critical programming languages such as C++ or Java.

• Experience with cloud platforms (e.g., AWS, Azure, GCP) for deploying scalable optimization solutions or high-performance computing (HPC) environments.

• Prior experience in defense, aerospace, logistics, supply chain management, robotics, or manufacturing optimization domains.

• Familiarity with integrating machine learning models with optimization techniques (e.g., prescriptive analytics, reinforcement learning for optimization).

• Excellent communication skills with the ability to articulate complex technical concepts, present findings, and influence technical direction across diverse teams.

• Willingness to travel up to approximately 10%.

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This role sits at the intersection of quantum hardware, systems engineering, and software infrastructure, ensuring that cross-disciplinary teams deliver integrated quantum systems on schedule.

As a Senior TPM, you will own the planning and execution of large technical programs that bring these components together into deployable quantum systems.

You will operate in a fast-moving deep-tech environment where many efforts are research-driven and technically ambiguous, requiring strong judgment, technical understanding, and execution discipline.

Program Leadership

• Own the end-to-end delivery of complex technical programs at the system level.
• Build and maintain program roadmaps, milestones, and integration schedules for quantum system releases.
• Drive execution across multiple engineering teams while maintaining alignment with company priorities.

Cross-Functional Execution

• Coordinate work between teams, including:
• Quantum device & fabrication
• Cryogenic, control hardware and software
• Manage dependencies and integration across the quantum computing stack.

Systems Integration

• Lead cross-team integration planning for new quantum processor generations and system deployments.
• Ensure alignment between research milestones and engineering deliverables.
• Track readiness across hardware, firmware, and software layers.

Risk & Decision Management

• Identify technical, schedule, and operational risks early.
• Facilitate data-driven decisions with engineering leadership.
• Drive resolution of cross-team blockers and competing priorities.

Operational Excellence

• Establish scalable program management practices for deep-tech R&D.
• Improve engineering planning, milestone tracking, and program reporting.
• Support leadership with clear program visibility and status reporting.

Required Qualifications

• 7+ years of experience in technical program management, engineering program management, or systems engineering.
• Experience delivering complex multidisciplinary technology programs.
• Strong understanding of hardware + software system development lifecycles.
• Demonstrated ability to lead programs across multiple specialized engineering teams.
• Exceptional communication and stakeholder management skills.
• Ability to operate effectively in ambiguous, research-driven environments.

Preferred Qualifications

• Experience in quantum computing, semiconductors, advanced hardware systems, or deep-tech startups.
• Background working with R&D organizations or research-to-product transitions.
• Experience with large-scale system integration programs.
• Familiarity with Agile or hybrid development models in hardware/software environments.
• Degree in Engineering, Physics, Computer Science, or related technical discipline

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Drawing from your expertise in circuit Quantum Electrodynamics and full-wave radio-frequency engineering, from fundamental theory through practical application, you will identify and implement improvements to the integrated circuit layout to mitigate loss and crosstalk channels. You will lay out and design microwave multi-qubit circuits for fabrication and develop next-generation quantum processors.

Key responsibilities include designing, laying out, and simulating superconducting microwave integrated circuits for quantum processors, with a focus on optimal on-chip signal delivery (routing, filtering, multiplexing, etc…). You will also simulate the full-wave electromagnetic performance of quantum processors (eigenmode & driven analyses) using commercial finite element software, engineering the mode profile of resonant structures and the coupling between these resonant structures and on-chip feedlines to optimize device performance.

Engagement with quantum engineers to identify and optimize Hamiltonian parameters for our R&D test devices and deployed quantum processors is also required. Additionally, you will map between target quantum Hamiltonians and integrated circuit layouts using internal python software libraries to construct and diagonalize the quantum Hamiltonian.

Interpretation of simulation and experimental results to identify and mitigate loss and crosstalk channels, or other undesirable microwave properties of the circuit, is essential. Collaboration with fabrication and experimental teams to develop novel processor architectures is also expected.

A PhD in Physics, Applied Physics, Electrical Engineering, or a related field, or the equivalent experience in industry and 3+ years of industry experience is preferred. Strong background in the theory and application of circuit Quantum Electrodynamics to the design of superconducting qubit based quantum processors is also required.

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In this role, you will define FPGA architectures, implement high-performance digital logic, and collaborate closely with hardware, firmware, and quantum engineering teams to build scalable, low-latency control systems.

Key responsibilities include: Developing and improving a custom microprocessor responsible for waveform generation and critical logic to operate a quantum computer Working closely with hardware, firmware, and software teams to define architecture, data flow, and interfaces Implementing, simulating, and verifying designs including DSP pipelines, control logic, and high-speed I/O Optimizing designs for latency, resource utilization, and robustness in production environments Developing and maintaining testbenches, verification flows, and CI Supporting bring-up, lab validation, and debugging in collaboration with Quantum Engineering on actual quantum computers Contributing to the long-term roadmap for the architecture of Rigetti’s control systems.

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We are looking for a Junior Recruiter to support our recruiting operations while developing long-term ownership of University and Early Career hiring. This role is well-suited for a recruiter who thrives in structured execution, enjoys working with deeply technical teams and is motivated to learn and grow in a highly specialized environment.

This role focuses on reliable execution, operational excellence, and skill development. The recruiter will work under the guidance of senior recruiters and leadership while independently owning defined recruiting activities and workflows, with increasing scope over time.

Responsibilities:

Recruiting Operations & Coordination

• Own interview scheduling for technical roles, coordinating across candidates, hiring managers, interviewers, and recruiting partners
• Maintain accurate, compliant, and well-organized candidate records in the Applicant Tracking System (ATS)
• Support job postings, candidate communications, interview logistics, and offer coordination
• Ensure a high-quality candidate experience through timely communication and operational follow-through
• Identify and flag scheduling risks, process gaps, or data quality issues to senior team members

University & Early Career Recruiting

• Support and gradually take ownership of University Recruiting programs, including internships and entry-level technical roles
• Partner with senior teammates to engage with universities, research programs, student organizations, and early-career talent communities
• Assist with planning and execution of career fairs, campus visits, conferences, and virtual information sessions, including occasional travel to support outreach and hiring initiatives
• Support creation and management of recruiting materials and event supplies, such as swag, handouts, presentations, and branded collateral, in partnership with Recruiting and Marketing teams
• Help manage intern and early-career hiring workflows from requisition through conversion
• Track and report on early-career recruiting metrics (e.g., pipeline health, interview outcomes, conversion rates)

Collaboration & Process Improvement

• Work closely with recruiters, hiring managers, and People team partners to support headcount planning and hiring priorities
• Contribute to continuous improvement of recruiting processes, templates, documentation, and tools
• Support special projects such as ATS clean-up & integrations, reporting improvements, or early-career program enhancements

Required Qualifications

• 2-4 years of experience in recruiting, recruiting coordination, or talent operations
• Familiarity with an Applicant Tracking System (ATS) (e.g., Lever, Greenhouse, Workday)
• Strong organizational skills with the ability to manage high-volume scheduling and operational tasks
• Clear and professional communication skills, both written and verbal
• Ability to partner effectively with highly technical stakeholders (e.g., engineering, research, manufacturing teams)
• Demonstrated attention to detail and accountability for deliverables
• Interest in quantum computing, physics, engineering, or advanced manufacturing environments

Nice-to-Haves

• Academic background in or familiarity with fields such as physics, engineering, materials science, or computer science
• Exposure to recruiting for technical roles in hardware, research, or lab-based environments
• Experience supporting internship, co-op, or new-graduate hiring programs
• Experience coordinating interviews across multiple time zones
• Experience in a startup, scale-up, or research-driven environment

Additional Information

As engineering leaders, we value diversity and are committed to building a culture of inclusion to attract and engage innovative thinkers. Our technology, meant to serve all of humanity, cannot succeed if those who built it do not mirror the diversity of the communities we serve. Applications from women, minorities, and other under-represented groups are encouraged.

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You will develop software infrastructure to streamline and automate these analyses to accelerate learning cycles. Finally, you will collaborate closely with researchers and engineers across Rigetti to monitor and improve fabrication yield, and improve the models and infrastructure used to predict processor performance from foundry metrology data.

Key responsibilities include designing and implementing industry-grade software infrastructure in Python to streamline feedback from measurement to the integrated circuit design team, identifying correlations between fabrication metrology data and processor performance through the analysis of empirical datasets, and utilizing techniques and best practices in statistical analysis and machine learning to accurately calibrate various processor design parameters.

Required qualifications include an undergraduate degree in Computer Science, Physics, Applied Physics, Electrical Engineering, or a related field, 6+ years of experience in data science and statistical analysis in a scientific field, and programming skills in Python for scientific applications.

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