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Requisition Number: 30293 Required Travel: 11 - 25% Employment Type: Full Time/Salaried/Exempt Anticipated Salary Range: $83,720.00 - $101,660.00 Security Clearance: Top Secret Level of Experience: Mid This opportunity resides with Global Security (GS). Mission Technologies' Global Security (GS) group comprises live, virtual, constructive (LVC) solutions; fleet sustainment; nuclear and environmental; and Australia business. As a trusted partner to our military customers, HII designs, develops and operates the largest LVC enterprise that prepares warfighters for cross-domain battle. With advanced technologies to enable mission readiness, HII understands that preparation requires full coordination-not readiness in piece-parts. For more than 40 years, the U.S. Navy has entrusted HII to maintain and modernize the vast majority of its fleet. With a holistic approach to life-cycle maritime defense systems-from small watercraft to submarines, surface combatants and aircraft carriers-HII ensures a high state of readiness. HII supports the Department of Energy's national security mission through the management and operation of its sites, as well as the safe cleanup of legacy waste across the country. HII meets clients' toughest nuclear and environmental challenges. Leadership Mindset at HII - Mission Technologies Leadership at HII is a mindset, not a title. Through our Leadership Capability Framework, we define how every employee grows, leads, and contributes-regardless of role. It sets the standard for how you can develop yourself and what you can expect from leaders across our organization. We look for candidates who want to grow in alignment with these capabilities: Know & Grow Your People - Commit to learning and supporting team success. Build Relationships - Communicate openly, collaborate well, and build trust. Take Ownership - Deliver on commitments and take pride in your work. Customer First - Focus on the mission and those we serve. Shape the Future - Bring ideas, curiosity, and continuous improvement. Act with Urgency - Take initiative and follow through with purpose. These capabilities guide how all employees contribute to our shared success across Mission Technologies. Who We Are Mission Technologies, a division of Huntington Ingalls Industries, is seeking an experienced Systems Application Analyst to support operations at the Navy Warfare Development Center located at Norfolk Naval Station.This position provides on site expertise to the Maritime Operations Center - Exercise Support Team (MOC EST) and other facilities throughout the Hampton Roads, Virginia area. In this position, the selected candidate will guide the development, execution, and ongoing enhancement of the organization's Knowledge Management (KM) program. They will ensure that essential institutional knowledge is properly captured, structured, governed, shared, and maintained to strengthen operational effectiveness, collaboration, training, and organizational learning. The candidate will also support Navy Live, Virtual, and Constructive (LVC) training across assigned Areas of Responsibility (AORs). This includes contributing to the planning, design, and execution of operational level Fleet Synthetic Training (FST O) events for Fleet and task force staffs, including reserve personnel. Regular engagement with Military, Government, and Contractor leadership is a key component of the role. What You Will Do Develop, manage, and continuously improve the enterprise Knowledge Management framework, strategy, standards, and governance processes. Lead KM initiatives and provide direction and guidance to KM team members, content owners, subject matter experts, and stakeholders. Identify, capture, organize, classify, maintain, and assess organizational knowledge assets. Design, configure, administer, and maintain Microsoft SharePoint sites, libraries, lists, pages, permissions, metadata, content types, workflows, and knowledge repositories. Develop and maintain web-based KM resources using HTML5, CSS3, and JavaScript, including responsive interfaces, navigation components, interactive content, and client-side functionality. Apply web development and user-experience principles to improve the accessibility, usability, and presentation of organizational knowledge. Coordinate with cross-functional organizations to align KM initiatives with operational processes, training programs, organizational learning, information governance, and business objectives. Promote the adoption of KM platforms, tools, standards, and processes to encourage knowledge sharing and collaboration. Establish content lifecycle and governance processes to ensure information remains accurate, authoritative, current, accessible, and appropriately controlled. Support the development and delivery of KM training, documentation, user guides, standards, and best practices. Identify barriers to knowledge sharing and organizational adoption and develop strategies to improve participation and KM culture. Evaluate emerging technologies and tools that can enhance enterprise search, collaboration, content management, automation, and knowledge discovery. Identify and communicate KM success stories, lessons learned, and best practices across the organization. What You Must Have 5 years relevant experience with Bachelors in related field; 3 years relevant experience with Masters in related field; 0 years experience with PhD or Juris Doctorate in related field; or High School Diploma or equivalent and 9 years relevant experience. Candidate must have experience developing KM programs within technology-focused organizations, technical teams, government organizations, or similarly complex environments. Candidate must have experience implementing and supporting SharePoint-based knowledge and collaboration solutions. Candidate must have experience developing or maintaining web-based information resources using HTML, CSS, and JavaScript. Candidate must have a strong understanding of knowledge lifecycle management, content governance, information architecture, taxonomy, metadata, search, and organizational learning. Candidate must have the ability to translate business and operational requirements into practical KM processes and technical solutions. Candidate must have experience communicating with and influencing senior leadership, stakeholders, technical teams, and subject matter experts. Candidate must have strong written, verbal, analytical, organizational, and presentation skills. Candidate must have experience leading teams and cross-functional initiatives to achieve measurable results. Candidate must be okay with routine travel to remote site facilities may be involved. Candidate must be okay with working non-standard hours may be required approximately 6 times per year for 2-3 weeks at a time to support event execution and testing. Candidate must be a U.S. Citizen. Candidate must currently hold and be able to maintain a US Top Secret clearance. Bonus Points For Having! Certified Knowledge Manager (CKM) or comparable Knowledge Management certification. CompTIA Security+ Microsoft SharePoint or Microsoft 365 certifications. Experience with Microsoft Power Platform technologies. Experience with enterprise content management, records management, or information governance programs. Experience designing KM solutions for large, distributed, government, defense, or technically complex organizations. Physical Requirements May require working in an office, industrial, shipboard, or laboratory environment. Capable of climbing ladders and tolerating confined spaces and extreme temperature variances. The listed salary range for this role is intended as a good faith estimate based on the role's location, expectations, and responsibilities. When extending an offer, HII's Mission Technologies division takes a variety of factors into consideration which include, but are not limited to, the role's function and a candidate's education or training, work experience, and key skills. Meet HII's Mission Technologies Division Our team of more than 7,000 professionals worldwide delivers all-domain expertise and advanced technologies in service of mission partners across the globe. Mission Technologies is leading the next evolution of national defense - the data evolution - by accelerating a breadth of national security solutions for government and commercial customers. Our capabilities range from C5ISR, AI and Big Data, cyber operations and synthetic training environments to fleet sustainment, environmental remediation and the largest family of unmanned underwater vehicles in every class. Find the role that's right for you. Apply today. We look forward to meeting you. To learn more about Mission Technologies, click here for a short video: HII is more than a job - it's an opportunity to build a new future. We offer competitive benefits such as best-in-class medical, dental and vision plan choices; wellness resources; employee assistance programs; Savings Plan Options (401(k ; financial planning tools . click apply for full job details

Astera Labs (NASDAQ: ALAB) provides rack-scale AI infrastructure through purpose-built connectivity solutions. By collaborating with hyperscalers and ecosystem partners, Astera Labs enables organizations to unlock the full potential of modern AI. Astera Labs' Intelligent Connectivity Platform integrates CXL , Ethernet, NVLink, PCIe , and UALink semiconductor-based technologies with the company's COSMOS software suite to unify diverse components into cohesive, flexible systems that deliver end-to-end scale-up, and scale-out connectivity. The company's custom connectivity solutions business complements its standards-based portfolio, enabling customers to deploy tailored architectures to meet their unique infrastructure requirements. Discover more at . Role Summary We are seeking a technically strong Chief of Staff to the Head of Engineering who will also lead Engineering Program Management across Silicon Engineering. This role is a force-multiplier for Engineering leadership - driving org scale, decision velocity, and execution rigor. The ideal candidate brings deep technical fluency, structured problem-solving, and the ability to drive outcomes through influence rather than hierarchy. The role is fully in person in San Jose. Responsibilities - What You Will Own 1) Chief of Staff to Head of Engineering • Drive operational cadence: engineering all hands, staff meetings, agenda/material prep, tech talks, university engagements, action follow-through, and leadership syncs. • Frame and resolve high-leverage decisions - proactively surface blockers (technical, operational, organizational) before they escalate. • Manage escalations and organizational friction - diagnose root causes, coordinate resolution paths, and ensure durable fixes. • Partner cross-functionally with Hardware, Product, and Quality teams to ensure clarity of communication, alignment on priorities, and disciplined follow-through on decisions. • Support org design, headcount planning, and hiring prioritization for engineering teams. • Maintain alignment across functions through clear messaging and communication, validate exitance and validation of processes • Navigate org dynamics, build trust, and constructively challenge assumptions; maintain psychological safety. • Support the head of engineering with administrative and org related activities 2) Lead ASIC Tape out Management (Silicon Programs) • Status management - collect and track status across functions contributing to ASIC tapeouts. • Milestone tracking - maintain methodology checklists and boundary agreements to ensure schedule adherence. • IP and vendor tracking - own visibility into IP deliveries, version inventory, vendor issues, and escalation loops. • Quality & documentation - monitor quality KPIs, ensure engineering documentation completeness. • Requirements tracking - ensure PRDs/features are captured, tracked, baselined. • Resource monitoring - track compute, hardware, storage consumption and thresholds. • Internal reporting - generate status reporting for Silicon Engineering leadership. 3) Influence Without Authority • Drive cross-engineering outcomes through credibility, clarity, and follow-through - not hierarchy. • Create order in ambiguous spaces; shape scope where it is undefined. Qualifications • 10+ years in semiconductor/SoC/ASIC or adjacent high-complexity engineering environment (e.g., CPU/IP/System companies). • Proven success in Chief of Staff, Staff Program Manager, TPM Director, or similar technical leadership-enablement role. • Strong technical acumen - able to understand engineering trade-offs and make decisions with limited information, challenge assumptions, and earn credibility with senior ICs. • Demonstrated experience running program cadence for complex silicon programs (tapeout, IP integration, etc.). • Proven ability to organize complex workflows and drive consistent follow-through. • High EQ and organizational awareness; can navigate tension and align diverse viewpoints. • Exceptional written/verbal communication, structured thinking, and execution discipline. • Prior experience in leading RTL2GDSII chip design is a huge plus. What Success Looks Like • Engineering leadership spends more time on strategic and technical decisions, less on coordination. • Milestones hit with fewer escalations and clearer accountability. • Status, risks, and decisions are crisp - never ad hoc or late. • Teams feel supported, not policed - trust increases, friction decreases without compromising on accountability . • Ambiguity decreases over time as clarity and execution rhythm scale with the org. Salary range is $216,000 to $300,000 depending on experience, level, and business need. This role may be eligible for discretionary bonus, incentives and benefits. We know that creativity and innovation happen more often when teams include diverse ideas, backgrounds, and experiences, and we actively encourage everyone with relevant experience to apply, including people of color, LGBTQ+ and non-binary people, veterans, parents, and individuals with disabilities.

Job Description Job Description ABOUT ROCKET LAB 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. SPACE SYSTEMS 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 PRINCIPAL SPACECRAFT OPERATIONS ENGINEER II- SECRET CLEARANCE Based on site at Rocket Lab's headquarters in Long Beach, CA the PrincipalSpacecraft Operations Engineer is responsible for ensuring the health, safety, and optimal performance of a growing fleet of satellites while meeting mission objectives and SLAs for both commercial and government customers. This includes supporting diverse missions such as LEO constellations, interplanetary exploration, LEO rendezvous, and SDA-related deployments. Your expertise would be critical during commissioning, orbit raising, routine operations, and potentially re-entry phases, ensuring the health and safety of Rocket Lab's expanding fleet. The Spacecraft Operations team works closely with related teams, such as spacecraft design, AIT, flight software, propulsion, GNC, flight dynamics and ground software development to help improve both the ground and satellite-based capabilities over time. The space operations experience at Rocket Lab is unique because you will cover a multitude of roles/positions and responsibilities, with the large majority of the technical products being supplied through the vertical integration/in-house. WHAT YOU'LL GET TO DO: Serve as the program's mission operations technical lead: set the technical direction and strategy for operations, plan and prioritize the work of the mission operations staff, and act as the primary operations point of contact for program-level design decisions and trades Advocate for operability across the program: influence spacecraft and ground architecture upstream so vehicles are designed to be operated safely, efficiently, and autonomously, and push for changes to program design and execution when operational needs demand it Own mission operations requirements and lead requirements validation and verification for spacecraft missions and system-level capability and function Define the automation strategy and lead the development of robust, software-driven methods for mission operations, testing, and data analysis to ensure efficient, repeatable, and reliable spacecraft operation Design, develop, and test flight software sequences and FDIR/telemetry configurations to ensure spacecraft health and fault management through software-driven processes Architect, develop, and test ground software for long-duration operations, including scripting and automation frameworks that make operations robust, hands-off, and scalable across a growing fleet Establish and steward the integration, testing, and maintenance of mission operations tooling and codebases, including CI, version control, and release discipline. Ensure the on-call or shift schedules of operations Author and own interface specifications, CONOPS, contingency procedures, and other operational design documents Lead validation of flight products and procedures against spacecraft simulation tools, including flatsat, HITL, SIL, and digital twins Support AIT teams across multiple spacecraft integrated tests (TVAC, propulsion stack, DITL Provide program and product support to team leads and program managers, and serve as a key technical interface between the NZ and USA engineering teams Represent mission operations in program milestone reviews, design reviews, and readiness gates, and drive continuous improvement through post-mission lessons learned YOU'LL BRING THESE QUALIFICATIONS AS A PRINCIPALSPACECRAFT OPERATIONS ENGINEER: Bachelor's degree in engineering (software, computer, electrical, aerospace, mechanical, or other technical engineering discipline) 12+ years of direct experience in any of the following: space mission design, satellite subsystems, ground systems, spacecraft command control, or spacecraft operations 5+ years of experience leading teams of engineers through spacecraft missions or related aerospace projects Previous experience in roles such as Mission Lead, Mission Director, Flight Director, or Senior Spacecraft Operations Engineer Previous experience supporting mission operations activities in an on-console or operator-in-the-loop capacity Thorough understanding of key spacecraft subsystems and associated components, including attitude determination and control systems (ADCS), electrical power systems (EPS), space-to-ground communications, command and data handling (C&DH), thermal control systems (TCS), spacecraft propulsion systems, and fault detection, isolation, and recovery (FDIR) Understanding of the space environment, orbital mechanics, and rigid body dynamics 5+ years of direct software development experience (Python/Ruby/C/C++/other high-level languages), covering items such as spacecraft onboard flight scripts, ground scripting and automation, and data manipulation and analysis US citizenship is required due to program requirements Active U.S. Government Secret Security Clearance THESE QUALIFICATIONS WOULD BE NICE TO HAVE: Master's or PhD engineering in engineering (software, computer, electrical, aerospace, mechanical, or other technical engineering discipline) Prior experience in spacecraft operations Prior experience in satellite system design Prior experience in satellite ground systems Exposure to modern development practices - GIT, CI/CD, cloud infrastructure Proficiency with Agile issue-tracking tools, specifically Jira, for mission task management, status tracking, and bug reporting Software-in-the-Loop (SIL) Testing: Exposure to testing frameworks that simulate software behavior in operational environments. Hardware-in-the-Loop (HIL) Testing: Familiarity with testing frameworks that integrate software and hardware systems. Active TS/SCI U.S. Government 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 Anticipated annual equity grant value is designed around function, level, experience, and other factors; realized value depends on vesting and stock-price performance. 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. Total Compensation (base and equity) $223,025-$339,400 USD Base Salary $173,300-$259,850 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. Important information: . click apply for full job details

Job Description Job Description Overview Test and Evaluation Manager (Principal) LOCATION: Wright-Patterson AFB, OH JOB STATUS: Full-time CLEARANCE: SECRET TRAVEL: 10-25% Astrion has an exciting opportunity for a Test and Evaluation Manager located at Wright-Patterson AFB, OH working with the Air Force Division. Join the team supporting the F-15 program-one of the most operationally lethal and enduring fighter aircraft platforms in the world. As the workhorse of the U.S. Air Force, the F-15 has proven itself as the most lethal and reliable combat aircraft in service, with unmatched speed, agility, and payload capacity. Our program team consists of dedicated, mission-focused professionals who bring technical expertise, operational insight, and a commitment to excellence in support of this critical national defense capability. Be part of a program that directly impacts air superiority, national defense, deterrence, and alliances across the world. REQUIRED QUALIFICATIONS / SKILLS Expert knowledge, experience and recognized ability to be considered an industry leader in their technical/professional field. Typically performs the following kinds of functions: initiates, oversees, and/or develops requirements from a project's inception to conclusion for complex to extremely complex programs; provides strategic advice, technical guidance, and expertise to program and project staff; provides detailed analyses, evaluations, and recommendations for improvements, optimization development, and/or maintenance efforts for client-specific or mission critical challenges/issues; consults with client to define needs or problems; oversees studies; and leads surveys to collect and analyze data to provide advice and recommend solutions. Have a minimum of ten (10) years of experience as a US military fighter/bomber, pilot, or weapons systems officer background and an understanding of 4th/5th generation fighter weapons systems integration operational employment and weapons capability and software development processes. Minimum of five (5) years of experience in test and evaluation/test management, to include software development, test planning, certification, and evaluation. Minimum of ten (10) years of experience supporting the requirements of the foreign partner through the FMS programs/policies. Possesses the ability to perform tasks and oversee the efforts of junior, journeyman, and senior contractor personnel within and across multiple technical/professional disciplines. 30 years of directly related experience with proper certifications, 20 years of which must be in the DoD, OR Bachelor's Degree in a related field and 25 years of experience in the respective technical/professional discipline being performed, 15 years of which must be in the DoD, OR Master's or Doctorate Degree in a related field and at least 20 years of experience in the respective technical/professional discipline being performed, 12 years of which must be in the DoD. PREFERRED QUALIFICATIONS / SKILLS Leadership experience in wide/varied operational and test organizations and fighter/bomber platforms; operational experience as a pilot or weapons system operator in a test environment; 4th generation fighter aircraft, systems, and subsystems familiarity; the ability to travel frequently for program reviews and/or site visits; and other airframe, system and sub-system Contractor, test range and laboratory, or customer locations as directed/required. Finish Ability to provide detailed analyses, evaluations, and recommendations for improvements, optimization development, and/or maintenance efforts for client-specific or mission critical challenges/issues. Have a general understanding of current DoD and USAF-specific acquisition regulations, guidelines, and processes. RESPONSIBILITIES Supports complex FMS test tasks coordinating and managing test planning, development and execution.

Job Description Job Description Who We Are: Aurelius Systems is a VC backed defense tech startup building autonomous, edge deployed directed energy systems for counter-UAS. We build laser weapons to shoot down drones. We're a small team of 10 engineers, former US military operators, and subject matter experts scaling America's directed energy dominance. The first cost effective, reliable and robust laser weapon system. Our namesake isn't an accident. Marcus Aurelius wrote about doing the work in front of you, every day, without excuses. Henry Ford didn't wait for permission to reinvent manufacturing. That's how we operate - small team, unreasonable output, no hiding behind the unachievable. In addition to our San Francisco lab, we opened our Detroit manufacturing hub and field test weekly on our own 400-acre private range. The Role and Your Impact: We need a Principal Hardware Engineer to bring senior technical judgment across Archimedes hardware. You are a highly experienced builder who has seen systems go the full way. From a working prototype to hardware that ships and survives in the field. You've done it more than once. You know where systems break, where teams get stuck, and how to keep both moving. This is a technical leadership seat, not a people management seat. Your role is to raise the level of the hardware org through experience, architectural judgment, and hands-on execution. You lead by example, you unblock hard problems, and you set the technical bar for how hardware gets designed and shipped at Aurelius. You'll partner with the founders and the Director of Engineering on architecture and roadmap. You'll work directly alongside mechanical, electrical, power, embedded, and optics engineers on the hardest problems the team is facing. What You'll Own: Architectural direction across the hardware stack from mechanical, electrical, power, to embedded integration Technical decisions on the hardest problems, from concept through production readiness Pattern recognition and technical review like surfacing risk early, and catching what junior engineers miss Handson execution when the problem needs your specific experience to solve fast Design and manufacturing trades across cost, mass, reliability, schedule, and field performance Cross-team judgment when hardware, controls, optics, and software collide Setting the technical bar for design reviews, documentation quality, and release standards Mentorship by example. Engineers should learn from watching you work, not from being managed by you What We're Looking For: 10+ years designing and shipping complex hardware systems Track record taking systems the full development cycle from prototype through manufacturing and deployment Senior IC or technical leadership background at hardware companies that actually shipped Deep technical judgment across at least two of: mechanical, electrical, power electronics, embedded systems Pattern recognition from having built real systems before, especially systems that had to survive real-world conditions Comfort operating as the technical anchor on a small team, not the manager of a large one Nice to Haves: Directed energy, laser, or high-power systems experience Defense or aerospace program experience with MIL-STD or equivalent qualification Founder or founding engineer background at a hardware company Manufacturing depth as-in you've stood up production lines or worked closely with the manufacturers who do Active security clearance or ability to obtain one How You Operate: Extreme bias for action. You'd rather build a prototype tomorrow than model it for a month You characterize your own systems before the field does Comfortable with ambiguity and fast iteration in a startup environment You debug from first principles, not intuition alone Clear communicator across mechanical, electrical, optical, and software teams Self directed. You identify what needs to happen next and do it without being told Why Join Aurelius Systems: Build more in 1 month than most engineers build in 1 year. We field test weekly. Your work goes downrange, not into a filing cabinet. Career velocity is real. At 10 engineers, there are no layers between you and impact. Work on a problem that actually matters. Small cheap drones are changing warfare. Our laser systems are the asymmetric answer - infinite magazine, near zero cost per shot, scalable to every base, border, facility, and truck. Join the densest defense startup ecosystem in the country. California is where the next generation of defense companies are being built. How We Work: Core hours are Monday through Friday, 9 to 6. When we're sprinting toward a demo or field test, the team ramps up - nights, weekends, whatever it takes to ship. When the sprint lands, we ramp down. We don't manufacture intensity for show. Benefits: Competitive salary and equity United Health Care medical, dental, and vision coverage Flexible 18 days PTO plus 5 sick days Travel to field test events and range days Covered daily lunches and office snacks and drinks E-bike and scooter stipend up to $500 Direct access to leadership and real ownership over your work Export Control Notice: This role requires access to export-controlled information or items that require U.S. Person status. As defined by U.S. law, individuals who are any one of the following are considered to be a U.S. Person: (1) U.S. citizens, (2) legal permanent residents (a.k.a. green card holders), and (3) certain protected classes of asylees and refugees, as defined in 8 U.S.C. 1324b(a)(3). Compensation Range: $255K - $305K

Job Description Job Description Staff / Principal Platform Engineer Location: New York City Hybrid Department: AI Platform & Infrastructure Team Reports to: Vangie Shue - Principal Engineering Manager About AppGate AppGate secures and protects an organization's most valuable assets with its high performance Zero Trust Network Access (ZTNA) solution and Cyber Advisory Services. AppGate ZTNA is the only direct-routed Zero Trust solution built for peak performance, superior protection and seamless interoperability. AppGate Cyber Advisory Services harden your security posture and ensure business continuity. AppGate safeguards Fortune 500 enterprises and government agencies worldwide. Learn more at About the Role As we expand our platform, we are standing up a new AI Platform & Infrastructure team: the engine room of AppGate's AI strategy. This team owns the infrastructure layer that every next-generation security capability is built on, from network observability to AI-driven threat detection and the secure operation of emerging Agentic AI systems. We're looking for a Staff or Principal Platform Engineer to build and operate the foundational platform behind AppGate's AI products. You combine deep DevOps and cloud infrastructure expertise with hands-on experience operationalizing AI/ML systems, and you treat observability as a first-class engineering discipline. This is a rare opportunity to join a small, private, high-impact company where your work directly shapes the architecture, reliability and core platform that defines the future of security. You'll own the platform spanning APIs, cloud and self-managed solutions and AI/ML infrastructure, and you'll make it fast, reliable and observable at scale. This is a high-leverage, hands-on role for a senior engineer who sets technical direction and still ships. Key Responsibilities Build the Platform: design, build and operate the cloud infrastructure, services and pipelines that AppGate's AI and cloud products run on. Strong experience with self-managed technologies (kafka, elasticsearch) and Kubernetes are a must. Infrastructure as Code & Deployment Orchestration: Terraform and Helm for cloud provisioning, service deployment and configuration management. Implement Observability: instrument APIs, cloud services and AI/ML infrastructure with metrics, logging, tracing and alerting, and define SLOs and operational health metrics that teams trust. Data Platform: real-time and batch data ingestion pipelines, feature stores and data quality. Integrations: third-party connectors, APIs and platform integrations. Operationalize AI/ML: build model serving and inference pipelines, experiment tracking and the MLOps tooling for deployment, versioning, drift monitoring and lifecycle management. Engineer for reliability & automation: apply SRE practices to reduce toil, improve resilience and keep latency and uptime within target across the platform. Automate everything - deliver infrastructure-as-code, CI/CD and self-service tooling so product teams ship safely and quickly. Set technical direction: define platform standards, architecture and best practices, and raise the engineering bar through design reviews and mentorship. Collaborate cross-functionally: partner with data scientists, product teams and leadership to align platform investment with AppGate's strategic vision. Required Qualifications Experience: extensive platform, infrastructure or SRE engineering experience, with a track record of operating production systems at scale. Staff-level candidates typically bring 8+ years and Principal-level candidates 12+ years, though we hire on demonstrated impact. DevOps depth: strong command of infrastructure-as-code (Terraform or equivalent), CI/CD, containers and orchestration (Docker, Kubernetes), and cloud platforms (AWS). Observability expertise: hands-on experience implementing observability across APIs, cloud services and distributed systems using tools such as Prometheus, Grafana, OpenTelemetry, the ELK stack or comparable, including SLO and error-budget practice. Data platform skills: familiarity with real-time and batch ingestion pipelines, feature stores and data quality at production scale. Engineering craft: fluency in a primary backend language (Python, Go or similar) and a strong bias toward automation, testing and reliable, maintainable systems. Leadership: a record of setting technical direction, leading complex initiatives across teams, mentoring senior engineers, while still being very hands-on. Mindset: pragmatic, rigorous and ownership-driven. You thrive in a small, fast-moving environment and enjoy building foundations others depend on. Preferred Qualifications AI/ML infrastructure: experience building or operating model serving, inference pipelines and MLOps tooling such as MLflow, Kubeflow, SageMaker or equivalent, including model deployment, versioning and drift monitoring. Networking & Zero Trust fundamentals: working knowledge of the network and routing layer beneath modern access solutions - TCP/IP, TLS, tunneling/overlay networks, packet routing and filtering, DNS and firewalling - and familiarity with Zero Trust Network Access (ZTNA) or adjacent domains (VPN, SDP, SASE, software-defined networking). You can reason about traffic paths, latency and throughput end-to-end, and instrument the network as a first-class observability signal. Compensation Staff: 185k-225k base Principal: 215k-270k base We offer performance bonuses and considerable equity. AppGate is An Equal Opportunity/Affirmative Action Employer and a federal contractor subject to the Rehabilitation Act of 1973 and the Vietnam Era Veterans Readjustment Assistance Act of 1974 as amended, and their corresponding regulations. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status, age or any other federally protected class. Further, AppGate is an affirmative action employer committed to taking positive steps to employ, advance in employment and otherwise afford equal employment opportunity to protected veterans and individuals with disabilities. In furtherance of AppGate's policy regarding affirmative action and equal employment opportunity, AppGate has developed a written affirmative action program. This program is available for review upon request by any applicant or employee during normal business hours by contacting the company's EEO Coordinator.

Sr. Staff AI Engineer At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One's AI technical leadership Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy 9 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $314,800 - $359,300 for Sr. Staff AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer Richmond, VA: $286,200 - $326,700 for Sr. Staff AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Staff AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Sr. Staff AI Engineer At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One's AI technical leadership Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy 9 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $314,800 - $359,300 for Sr. Staff AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer Richmond, VA: $286,200 - $326,700 for Sr. Staff AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Staff AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Sr. Staff AI Engineer At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One's AI technical leadership Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy 9 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $314,800 - $359,300 for Sr. Staff AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer Richmond, VA: $286,200 - $326,700 for Sr. Staff AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Staff AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver -to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. The Simulator Team at Waymo builds state-of-the-art simulations of realistic environments for testing, training, and validation of the Waymo Driver. Our team is a diverse, and collaborative group of machine learning (ML) engineers, software engineers, and ML research engineers. We develop industry-leading simulation solutions using advanced generative and reconstructive ML algorithms, to model the real world, encompassing realistic agents, roads, traffic systems, weather, and the full sensor suite (Camera, Lidar, Radar). To accelerate the fidelity, scalability, controllability, and richness of our simulations, we are pushing the frontiers of 3D world modeling. We leverage state-of-the-art ML technologies trained on large-scale datasets to create dynamic and semantically rich virtual worlds, directly impacting the development and validation of the Waymo Driver. In this role, you will report to a Senior Staff Engineering Manager. You will: Lead the design, development and deployment of cutting-edge 4D world models and generative systems for ultra-realistic and controllable sensor and semantics generation for simulation use cases at waymo. Architect and implement scalable and robust ML pipelines for training, evaluating, and deploying large-scale generative models into our simulation infrastructure, including techniques like model distillation and quantization. Build and scale production-ready video generation techniques (e.g., Diffusion, Flow Matching) to create dynamic and interactive simulation environments. Apply Vision Language Models (VLMs) to enhance the semantic understanding and controllability of our world simulation products. Partner with world class research teams across Waymo and Alphabet to leverage State-of-The-Art research in 4D world modeling and generative AI into robust, production-ready solutions. Mentor and provide technical guidance to other engineers on the team. You have: MS or PhD in Computer Science, Machine Learning, Robotics, or a related field. 5+ years of experience in ML engineering and applied Deep Learning, with a strong portfolio of shipped products or publication record. Proven experience in developing and training large-scale generative models for video generation (e.g., Diffusion models, Flow Matching) or Vision Language Models (VLMs) and their applications. Deep expertise in 3D World Modeling or 3D computer vision. Familiarity with 3D reconstruction and rendering techniques (e.g., 3D Gaussian Splatting). Strong programming skills in Python and experience with ML frameworks such as Jax/Flax, PyTorch or Tensorflow. We prefer: PhD and a strong track record of delivering impactful ML products in 3D generative models, world models, or video generation Experience in simulating sensor data (Camera, Lidar, Radar) and/or semantic scenes. Experience with autonomous systems, robotics, or autonomous vehicle simulation. Experience in training and optimizing large scale models on GPU/TPU clusters for efficient serving. Experience in C++ for production systems. The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $213,000-$263,000 USD

Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver -to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. Onboard Software Performance team ensures that systems running on ADV (Autonomously Driven Vehicle) meet strict performance requirements such as producing necessary outputs within strict latency targets and using an appropriately allocated amount of compute resources (CPU/GPU/TPU/RAM etc) for each respective submodule. All of this needs to be done at scale with performance guarantees of many 9s of reliability while enabling high velocity of system evolution. In this hybrid role, you will report to a Senior Staff Engineer, Technical Lead Manager. You will: Develop ADV's modular architecture improvements and frameworks that maximize performance and compute utilization and ROI for driving quality Evolve our compute usage on the car and simulation to enable continued scaling where the system runs fast on the car and efficiently in our data center Collaborating with onboard teams to identify and improve compute performance bottlenecks across the stack to improve performance/driving quality Collaborating with hardware teams to codesign hardware/software and optimize the software for best performance on our hardware platform Ensuring our performance is strong at any driving complexity including as we scale to even more complex driving environments and encounter rarer events Ensuring state of the art reaction latency for collision avoidance via novel system/architecture designs and extremely fast nominal performance Developing necessary high scale performance evaluation, debugging and software change management processes Optimizing system resource usage to simulation at scale in Cloud datacenters: minimizing CPU utilization and latency, minimizing RAM consumption, intelligently determining which computations should happen on CPU, GPU, and TPU. You have: BS/MS in Comp Sci, EE, Robotics, Physics, Math, or related field (or equivalent experience) 6 years of software engineering experience on large scale/high complexity system (supported by hundreds of engineers) 2 years of software management experience with at least 4 years in infrastructure/systems/performance domain optimizing end to end system for high performance metrics 4 years of experience acting as technical lead in performance/software infrastructure domain 4 years of experience in C++ Define roadmap/portfolio of projects optimizing for end results overall across all aspects of the problem space Setup collaboration structures across team boundaries We prefer: Experience in robotics Experience in low level optimization techniques, frameworks (SIMD/CUDA) and ML performance/frameworks Experience in large scale evaluation techniques/data science and building performance metrics/tooling Experience in large scale software re-architecture projects The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $238,000-$302,000 USD

Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver -to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. The Waymo Driver is performing well in more and more cities, with our scale rapidly accelerating. Our team's job is to ensure that we can continue to evaluate safety and service quality across new cities and countries, each with their unique challenges. We need an experienced, technically hands-on engineering manager with strong quantitative skills to lead a small team and work with partners to scale eval and ML development by exploring new methods and delivering tools for mining and sampling data.In this hybrid role, you will report to a Senior Staff manager. You will: Develop tools for easy mining of novel situations that might impact safety from our driving logs for use in evaluation and ML datasets, using a mixture of ML and structured data Advanced sampling techniques and tuning of simulations to get strong signal for metrics and models from our datasets Build automation for our mining and sampling ecosystem so Waymo can rapidly scale to new cities Make hands-on technical contributions to both engineering and data science-oriented projects Provide strong management and technical leadership for a small team of data science-friendly engineers Partner with leads and teams across Waymo to determine and execute on strategy, including product, engineering, data science, frontend, and backend You have: Strong engineering design and programming skills Strong data fluency and analysis skills Familiarity with statistical methods including hypothesis testing, experiment design, and sampling Familiarity with foundational and contemporary ML concepts and practices Experience managing teams of up to 8 people BS/MS in Computer Science, Robotics, Statistics, Physics, Math, or other quantitative area 7+ years of industry experience with: C++, SQL, and Python experience Navigating and modifying a large code base containing C++, SQL, and Python Building data processing pipelines We prefer: Eval experience, such as building and validating metrics to measure quality in complex systems Strong statistical background (MSc-level stats or similar expertise from work experience) Strong ML background (MSc-level ML or similar expertise from work experience) Experience working in the AV industry and/or with simulations The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $281,000-$356,000 USD

Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver -to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. The Waymo Driver is performing well in more and more cities, with our scale rapidly accelerating. Our team's job is to ensure that we can continue to evaluate safety and service quality across new cities and countries, each with their unique challenges. We need an experienced, technically hands-on engineering manager with strong quantitative skills to lead a small team and work with partners to scale eval and ML development by exploring new methods and delivering tools for mining and sampling data.In this hybrid role, you will report to a Senior Staff manager. You will: Develop tools for easy mining of novel situations that might impact safety from our driving logs for use in evaluation and ML datasets, using a mixture of ML and structured data Advanced sampling techniques and tuning of simulations to get strong signal for metrics and models from our datasets Build automation for our mining and sampling ecosystem so Waymo can rapidly scale to new cities Make hands-on technical contributions to both engineering and data science-oriented projects Provide strong management and technical leadership for a small team of data science-friendly engineers Partner with leads and teams across Waymo to determine and execute on strategy, including product, engineering, data science, frontend, and backend You have: Strong engineering design and programming skills Strong data fluency and analysis skills Familiarity with statistical methods including hypothesis testing, experiment design, and sampling Familiarity with foundational and contemporary ML concepts and practices Experience managing teams of up to 8 people BS/MS in Computer Science, Robotics, Statistics, Physics, Math, or other quantitative area 7+ years of industry experience with: C++, SQL, and Python experience Navigating and modifying a large code base containing C++, SQL, and Python Building data processing pipelines We prefer: Eval experience, such as building and validating metrics to measure quality in complex systems Strong statistical background (MSc-level stats or similar expertise from work experience) Strong ML background (MSc-level ML or similar expertise from work experience) Experience working in the AV industry and/or with simulations The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $281,000-$356,000 USD

Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver -to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. The Waymo Driver is performing well in more and more cities, with our scale rapidly accelerating. Our team's job is to ensure that we can continue to evaluate safety and service quality across new cities and countries, each with their unique challenges. We need an experienced, technically hands-on engineering manager with strong quantitative skills to lead a small team and work with partners to scale eval and ML development by exploring new methods and delivering tools for mining and sampling data.In this hybrid role, you will report to a Senior Staff manager. You will: Develop tools for easy mining of novel situations that might impact safety from our driving logs for use in evaluation and ML datasets, using a mixture of ML and structured data Advanced sampling techniques and tuning of simulations to get strong signal for metrics and models from our datasets Build automation for our mining and sampling ecosystem so Waymo can rapidly scale to new cities Make hands-on technical contributions to both engineering and data science-oriented projects Provide strong management and technical leadership for a small team of data science-friendly engineers Partner with leads and teams across Waymo to determine and execute on strategy, including product, engineering, data science, frontend, and backend You have: Strong engineering design and programming skills Strong data fluency and analysis skills Familiarity with statistical methods including hypothesis testing, experiment design, and sampling Familiarity with foundational and contemporary ML concepts and practices Experience managing teams of up to 8 people BS/MS in Computer Science, Robotics, Statistics, Physics, Math, or other quantitative area 7+ years of industry experience with: C++, SQL, and Python experience Navigating and modifying a large code base containing C++, SQL, and Python Building data processing pipelines We prefer: Eval experience, such as building and validating metrics to measure quality in complex systems Strong statistical background (MSc-level stats or similar expertise from work experience) Strong ML background (MSc-level ML or similar expertise from work experience) Experience working in the AV industry and/or with simulations The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $281,000-$356,000 USD

Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver -to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. The Driver Understanding and Evaluation team at Waymo develops a rich understanding of Waymo Driver's behavior. With over 1 million driverless miles per week, it is critical that Waymo can understand and assess the behavior of all its vehicles - both in the field and in simulation - with automated algorithms. The learned metrics team is a strategic bet to use machine learning to ensure we can scale to meet Waymo's goals. We collaborate across teams to bring ML to production systems and build what is Waymo's reward function. We build and operate large-scale machine learning and data systems, simulation workflows, and insight tools. We combine expert human judgements and advanced machine learning models to deliver training and evaluation data for the Waymo driver. We are looking for researchers and software engineers who are passionate about developing production grade machine learning systems for our autonomous vehicles and have an incessant drive to improve the performance of our technology stack. This role follows a hybrid work schedule and reports to an Engineering Manager. You will: Lead a top-tier applied ML team focused on building ML models for AV behavior understanding and evaluation, using deep learning and Gen AI. Lead the development of cutting edge Deep Learning and machine learning models to enhance human-led triaging and introduce automation for high-volume workflows Design and build Gen AI LLM/VLM solutions for self driving car behavior analysis and anomaly detection Enhance User Feedback Analysis, collaborate seamlessly with product and business teams to design and implement tools for multi-label classifications, sentiment assessment, comment summarization, root cause analysis and trend analysis of rider feedback Oversee the production and optimization of machine learning models aiming to assess Waymo's expansive fleet of vehicles that cumulatively travel millions of miles. Drive technical direction, and provide technical inputs and guidance to the team. Work closely with PMs and TPMs to help define product requirements and align the technical agenda with the company's business objectives. Collaborate closely with multiple teams (e.g., Prediction, Planning, Research), other technical leads, and senior leaderships across Waymo to deliver on key strategic efforts. You have: B.S. in Computer Science, Robotics, Machine Learning, similar technical field of study, or equivalent practical experience 5+ years of experience leading engineering teams of 5-15 people 7+ years of experience with hands-on experience in machine learning projects 7+ years of hands-on experience building and deploying machine learning products in production environments Experience in at least one of: Foundational Models, VLM, Deep Learning Strong coding experience in C++ and/or Python. Experience with ML frameworks such as TensorFlow, PyTorch, Hugging Face's transformers, along with expertise in deep learning models and ML deployment at scale We prefer: M.S. or Ph.D. degree Computer Science or related quantitative field with a specialization of machine learning. Deep learning experience with Transformers Gen AI LLM/VLM experience Experience with building tools for applied machine learning, including MLOps, evaluation/validation techniques, and model performance optimization. Large-scale data processing and analytical skills. The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $238,000-$302,000 USD

Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver -to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. The Driver Understanding and Evaluation team at Waymo develops a rich understanding of Waymo Driver's behavior. With over 1 million driverless miles per week, it is critical that Waymo can understand and assess the behavior of all its vehicles - both in the field and in simulation - with automated algorithms. The learned metrics team is a strategic bet to use machine learning to ensure we can scale to meet Waymo's goals. We collaborate across teams to bring ML to production systems and build what is Waymo's reward function. We build and operate large-scale machine learning and data systems, simulation workflows, and insight tools. We combine expert human judgements and advanced machine learning models to deliver training and evaluation data for the Waymo driver. We are looking for researchers and software engineers who are passionate about developing production grade machine learning systems for our autonomous vehicles and have an incessant drive to improve the performance of our technology stack. This role follows a hybrid work schedule and reports to an Engineering Manager. You will: Lead a top-tier applied ML team focused on building ML models for AV behavior understanding and evaluation, using deep learning and Gen AI. Lead the development of cutting edge Deep Learning and machine learning models to enhance human-led triaging and introduce automation for high-volume workflows Design and build Gen AI LLM/VLM solutions for self driving car behavior analysis and anomaly detection Enhance User Feedback Analysis, collaborate seamlessly with product and business teams to design and implement tools for multi-label classifications, sentiment assessment, comment summarization, root cause analysis and trend analysis of rider feedback Oversee the production and optimization of machine learning models aiming to assess Waymo's expansive fleet of vehicles that cumulatively travel millions of miles. Drive technical direction, and provide technical inputs and guidance to the team. Work closely with PMs and TPMs to help define product requirements and align the technical agenda with the company's business objectives. Collaborate closely with multiple teams (e.g., Prediction, Planning, Research), other technical leads, and senior leaderships across Waymo to deliver on key strategic efforts. You have: B.S. in Computer Science, Robotics, Machine Learning, similar technical field of study, or equivalent practical experience 5+ years of experience leading engineering teams of 5-15 people 7+ years of experience with hands-on experience in machine learning projects 7+ years of hands-on experience building and deploying machine learning products in production environments Experience in at least one of: Foundational Models, VLM, Deep Learning Strong coding experience in C++ and/or Python. Experience with ML frameworks such as TensorFlow, PyTorch, Hugging Face's transformers, along with expertise in deep learning models and ML deployment at scale We prefer: M.S. or Ph.D. degree Computer Science or related quantitative field with a specialization of machine learning. Deep learning experience with Transformers Gen AI LLM/VLM experience Experience with building tools for applied machine learning, including MLOps, evaluation/validation techniques, and model performance optimization. Large-scale data processing and analytical skills. The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $238,000-$302,000 USD

Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver -to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. The Driver Understanding and Evaluation team at Waymo develops a rich understanding of Waymo Driver's behavior. With over 1 million driverless miles per week, it is critical that Waymo can understand and assess the behavior of all its vehicles - both in the field and in simulation - with automated algorithms. The learned metrics team is a strategic bet to use machine learning to ensure we can scale to meet Waymo's goals. We collaborate across teams to bring ML to production systems and build what is Waymo's reward function. We build and operate large-scale machine learning and data systems, simulation workflows, and insight tools. We combine expert human judgements and advanced machine learning models to deliver training and evaluation data for the Waymo driver. We are looking for researchers and software engineers who are passionate about developing production grade machine learning systems for our autonomous vehicles and have an incessant drive to improve the performance of our technology stack. This role follows a hybrid work schedule and reports to an Engineering Manager. You will: Lead a top-tier applied ML team focused on building ML models for AV behavior understanding and evaluation, using deep learning and Gen AI. Lead the development of cutting edge Deep Learning and machine learning models to enhance human-led triaging and introduce automation for high-volume workflows Design and build Gen AI LLM/VLM solutions for self driving car behavior analysis and anomaly detection Enhance User Feedback Analysis, collaborate seamlessly with product and business teams to design and implement tools for multi-label classifications, sentiment assessment, comment summarization, root cause analysis and trend analysis of rider feedback Oversee the production and optimization of machine learning models aiming to assess Waymo's expansive fleet of vehicles that cumulatively travel millions of miles. Drive technical direction, and provide technical inputs and guidance to the team. Work closely with PMs and TPMs to help define product requirements and align the technical agenda with the company's business objectives. Collaborate closely with multiple teams (e.g., Prediction, Planning, Research), other technical leads, and senior leaderships across Waymo to deliver on key strategic efforts. You have: B.S. in Computer Science, Robotics, Machine Learning, similar technical field of study, or equivalent practical experience 5+ years of experience leading engineering teams of 5-15 people 7+ years of experience with hands-on experience in machine learning projects 7+ years of hands-on experience building and deploying machine learning products in production environments Experience in at least one of: Foundational Models, VLM, Deep Learning Strong coding experience in C++ and/or Python. Experience with ML frameworks such as TensorFlow, PyTorch, Hugging Face's transformers, along with expertise in deep learning models and ML deployment at scale We prefer: M.S. or Ph.D. degree Computer Science or related quantitative field with a specialization of machine learning. Deep learning experience with Transformers Gen AI LLM/VLM experience Experience with building tools for applied machine learning, including MLOps, evaluation/validation techniques, and model performance optimization. Large-scale data processing and analytical skills. The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $238,000-$302,000 USD

Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver -to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. The Perception Team at Waymo builds the system that "sees" the world around the self-driving car. We conduct novel research to address real-world perception problems and collaborate with research teams at Alphabet. Here at Waymo, we have access to millions of miles of driving data from a diverse set of sensors, enabling researchers like you to develop complex models and techniques at scale. Improvements deployed to our system can immediately advance our large fleet of autonomous vehicles. Within Perception, the Sensor Health team's job is to make sure that sensors "just work" for the entire self-driving car software stack. We make sure that all sensors are properly calibrated and consistently monitored at all times. We process data from next-generation sensors on next-generation vehicle platforms and work closely with both hardware and software teams to provide the best possible sensor data from our sensors to our upstream customers. To this end, we develop sensor data alignment and calibration algorithms, a growing sensor health backend, and deploy our systems both into the Waymo Driver and our log processing backend. In this hybrid remote/in-office role, you will report to a Senior Staff TLM. You will: Lead and build a team of ML engineers in charge of reliable sensing anomaly detection and calibration Build a data flywheel to automatically generate suitable training data for rare instance sensor degradation events using VLMs Own the entire sensor validation stack end to end Drive and accelerate collaborations between perception, system engineering, evaluation, and Alphabet teams You have: MS in Computer Science, Robotics, Math, Physics or equivalent industry experience 6+ years of experience in designing, training, and deploying ML-driven real-time robotics systems 4+ years of experience leading technical teams and setting technical directions 2+ years of people management experience We prefer: PhD in Computer Science, Robotics, Math, Physics, or a related technical field Experience in robotics, autonomous systems, or related automotive industries. Experience with various sensor modalities (e.g., LiDAR, radar, cameras) and their unique challenges. Familiarity with early fusion multi modal sensor models and their development challenges Experience with rare instance or zero-shot detection problems The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $238,000-$302,000 USD

Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver -to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. The Perception Team at Waymo builds the system that "sees" the world around the self-driving car. We conduct novel research to address real-world perception problems and collaborate with research teams at Alphabet. Here at Waymo, we have access to millions of miles of driving data from a diverse set of sensors, enabling researchers like you to develop complex models and techniques at scale. Improvements deployed to our system can immediately advance our large fleet of autonomous vehicles. Within Perception, the Sensor Health team's job is to make sure that sensors "just work" for the entire self-driving car software stack. We make sure that all sensors are properly calibrated and consistently monitored at all times. We process data from next-generation sensors on next-generation vehicle platforms and work closely with both hardware and software teams to provide the best possible sensor data from our sensors to our upstream customers. To this end, we develop sensor data alignment and calibration algorithms, a growing sensor health backend, and deploy our systems both into the Waymo Driver and our log processing backend. In this hybrid remote/in-office role, you will report to a Senior Staff TLM. You will: Lead and build a team of ML engineers in charge of reliable sensing anomaly detection and calibration Build a data flywheel to automatically generate suitable training data for rare instance sensor degradation events using VLMs Own the entire sensor validation stack end to end Drive and accelerate collaborations between perception, system engineering, evaluation, and Alphabet teams You have: MS in Computer Science, Robotics, Math, Physics or equivalent industry experience 6+ years of experience in designing, training, and deploying ML-driven real-time robotics systems 4+ years of experience leading technical teams and setting technical directions 2+ years of people management experience We prefer: PhD in Computer Science, Robotics, Math, Physics, or a related technical field Experience in robotics, autonomous systems, or related automotive industries. Experience with various sensor modalities (e.g., LiDAR, radar, cameras) and their unique challenges. Familiarity with early fusion multi modal sensor models and their development challenges Experience with rare instance or zero-shot detection problems The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $238,000-$302,000 USD

Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver -to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. Software Engineering builds the brains of Waymo's fully autonomous driving technology. Our software allows the Waymo Driver to perceive the world around it, make the right decision for every situation, and deliver people safely to their destinations. We think deeply and solve complex technical challenges in areas like robotics, perception, decision-making and deep learning, while collaborating with hardware and systems engineers. If you're a software engineer or researcher who's curious and passionate about Level 4 autonomous driving, we'd like to meet you. The Sensor Foundations Team's purpose is to provide cleaned-up sensor data through highly optimized APIs to Perception models, to abstract sensor hardware differences where possible, and to provide low-level Perception signals either through algorithms or machine learning. Projects on our team typically require a diverse skill set, including robotics, system integration, code optimization, and machine learning. We have a good understanding of the hardware (both sensors and compute) and the overall Perception system. The Optimization sub-team uses our know-how of CPUs, GPUs, and clever algorithms to process Waymo's sensor data super-fast and feed it to the Perception ML models. We specialize in low-level understanding of compute hardware, and we apply that knowledge wherever we can, throughout the whole stack. We are looking for a Tech-Lead Manager with a CPU, GPU, or system-level optimization background to lead this small team of Software Engineers. Depending on your prior experience, you may also be responsible for system-level optimization and be a steward of our compute resources. This role follows a hybrid work schedule and reports to the TLM of the Sensor Foundations team. You will: Lead a small team of optimization experts Identify system-level optimization opportunities Optimize existing CPU code Write and review CUDA code Collaborate with ML practitioners to understand their input-processing needs. Be a steward of our compute resources You have: B.Sc in Computer Science, Mathematics or a related field 8+ years of industry experience Strong C++ programming skills Experience with optimizing CPU or GPU code (ideally both) Prior people management experience We prefer: M.Sc or PhD in Computer Science, Mathematics or a related field Experience with system-level optimization Experience with compiler technology. The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $298,000-$368,000 USD