Software Engineer L2 Cloud Infrastructure Salary Guide in United States

About the Team Our Robotics team is focused on unlocking general-purpose robotics and pushing towards AGI-level intelligence in dynamic, real-world settings. Working across the entire model stack, we integrate cutting-edge hardware and software to explore a broad range of robotic form factors. We strive to seamlessly blend high-level AI capabilities with the constraints of physical systems to improve peoples’ lives. About the Role We are seeking a Mechanical Engineer to lead the engineering, characterization, and productionization of flexible and compliant components in robotic platforms. You will partner closely with cross-functional teams to translate material concepts into engineered subsystems that meet functional, durability, and manufacturing requirements. This role focuses on understanding how soft materials behave in dynamic mechanical systems — including fatigue, creep, hysteresis, wear, and environmental degradation — and designing assemblies that perform consistently at scale. You will work with materials such as elastomers, foams, thermoplastic polyurethanes (TPUs), engineered fabrics, knitted and woven textiles, cables, and other flexible load-bearing or transmission elements, integrating them with rigid hardware, sensors, and actuators using fabrication methods such as bonding, molding, lamination, and sewn assemblies. This role is based in San Francisco, CA, and requires in-person presence 4 days a week. In this role, you will Design and integrate compliant or flexible materials into mechanical subsystems and rigid hardware interfaces. Leverage FEA tools to characterize material behavior under operational loads, including tension, compression, abrasion, fatigue, and environmental exposure. Develop test methods and validation protocols to evaluate durability, performance, and failure modes of soft components. Collaborate with cross-functional teams to transition early prototypes into manufacturable designs. Source and evaluate materials in collaboratio

About the team The Codex Deployment Engineering team helps customers adopt OpenAI's coding tools throughout their software development lifecycle. We act as trusted technical partners, guiding engineering teams as they integrate Codex into their projects and workflows. Our customers span digital-native companies to global enterprises, and we work side-by-side to accelerate how they plan, build, and deliver software. About the Role We are seeking a technically deep, creativity-driven AI Deployment Engineer who is already a power user of AI coding tools and passionate about pushing the boundaries of developer productivity. You will partner directly with engineering leaders and hands-on builders to design, validate, and scale advanced AI workflows, often using Codex to prototype and build the very demos, integrations, and automations customers ultimately adopt. This is a highly cross-functional role that blends technical architecture, product strategy, and customer-facing leadership. You’ll work closely with Sales, Solutions Engineering, Product, Applied Engineering, and the broader Codex organization to advocate for customer needs, shape product direction, and accelerate the successful deployment of intelligent coding systems across some of the world’s most influential companies. In this role, you will: Serve as the primary technical subject matter expert on OpenAI Codex for a portfolio of customers, embedding deeply with them to enable their engineering teams and build coding workflows. Partner directly with customers to design and implement AI-enhanced development workflows, from rapid prototyping through scalable production rollout. Build high-quality demos, reference implementations, and workflow automations, using Codex itself as part of your development process. Lead large-format workshops, technical deep dives, and hands-on enablement sessions that help engineering organizations adopt AI coding tools effectively and safely. Contribute technical content including

About the Team The OpenAI Robotics team is focused on unlocking general-purpose robotics and pushing towards AGI-level intelligence in dynamic, real-world settings. Working across the entire model stack, we integrate cutting-edge hardware and software to explore a broad range of robotic form factors. We strive to seamlessly blend high-level AI capabilities with the constraints of physical systems to improve peoples’ lives. About the Role OpenAI Robotics depends on high-quality real-world robot data from a large, live operational environment. That environment has many deployed workcells, changing configurations, and little tolerance for downtime. We are seeking a Field Engineer to help keep that environment running well. You will own the day-to-day technical health of robotic workcells used in ongoing data acquisition operations, diagnose and resolve failures across hardware and software, and build the practical tools, documentation, and support workflows that make operators and technicians more effective. The work is close to the floor, close to the failure modes, and close to the research impact. This role sits at the intersection of software, robotics hardware, and live operations. The best people in it are practical, technically sharp, calm under pressure, and motivated by making real systems work reliably at scale. This role will be based in San Francisco, CA 5 days per week and offer relocation assistance to new employees. In this role, you will: Serve as an engineering owner for keeping a fleet of robotic workcells online in daily operation. Diagnose, fix, mitigate, or escalate issues spanning mechanics, electronics, controls, software interfaces, logs, and configuration. Partner closely with technicians, operators, and engineering teams to improve scalable fleet support processes. Build or spec lightweight hardware and software tools that improve monitoring, diagnostics, recovery, and handoffs. Create documentation, SOPs, and diagnostic playbooks that turn en

The Research Engineer – Mechatronics is a hands-on engineering role within the TaylorMade Research & Development team, focused on the design, prototyping, integration, and validation of electromechanical systems that advance golf equipment and player performance. This role demands deep practical expertise in mechatronics, sensor systems, electronic hardware, wiring, and embedded controls, combined with the ability to develop supporting software and user-facing tools. The ideal candidate is a builder and problem-solver who thrives in a laboratory and prototype environment, producing functional systems from concept through deployment. Essential Functions and Key Responsibilities: Design, prototype, wire, assemble, and test mechatronic and electromechanical systems used in golf equipment evaluation, performance measurement, and product development Develop and interpret wiring diagrams, schematics, and electrical specifications for custom hardware assemblies, test rigs, and IoT-connected devices Select, integrate, and characterize sensors (IMUs, load cells, encoders, pressure sensors, optical sensors, etc.) – including defining operating limits, calibration procedures, and signal conditioning requirements Design and implement IoT systems and wireless data acquisition platforms that capture real-time performance data from equipment and players Develop embedded firmware and control software for microcontrollers and microprocessors (e.g., Arduino, Raspberry Pi, STM32 or similar) to drive test automation and data capture systems Write clean, maintainable code to interface with hardware, process sensor data, and build internal and user-facing applications and interfaces; leverage AI-assisted development tools to accelerate prototyping and automate test routines; apply basic computer vision techni

The Best Players Need the Best People. This role implements practical, AI-enabled workflows that increase productivity, reduce manual effort, improve speed, and deliver measurable business value across PGA Tour departments. Working closely with internal stakeholders including product teams, engineering, data science and AI COE, cybersecurity, privacy, technology operations, and approved vendors. The Forward Deployed Engineer documents existing workflows, defines requirements, configures approved tools with the AI Governance Committee, and supports rollout of repeatable solutions that are secure, accurate, reliable, and easy for employees to use. This is an implementation-focused role centered on assigned use cases and department-level workflow improvements. The engineer evaluates whether a business need can be met through existing enterprise platforms, configuration, integration, workflow redesign, or vendor capability, and will escalate larger product, roadmap, architecture, or custom-development decisions to AI leadership. Qualifications Bachelor’s degree in Computer Science, Information Technology, Data Science, Engineering, or equivalent practical experience. Minimum 5 years of experience in software engineering, systems integration, solutions engi

Leidos has an exciting opportunity for a Principal DevOps Engineer in our Intel Security Sector's Analysis Solutions Business Area . Our talented team is at the forefront in Security Engineering, Computer Network Operations (CNO), Mission Software, Analytical Methods and Modeling, Signals Intelligence (SIGINT), and Cryptographic Key Management. At Leidos , we offer competitive benefits , including Paid Time Off, 11 paid Holidays, 401K with a 6% company match and immediate vesting, Flexible Schedules, Discounted Stock Purchase Plans, Technical Upskilling, Education and Training Support, Parental Paid Leave, and much more. Join us and make a difference in National Security! Job Summary This Principal DevOps Engineer role provides mission critical system support to our customer. You will closely work with the Development team as well as other technology stakeholders to maintain, develop and support IC enterprise products – legacy and new products – in an Agile SAFe environment. The role will also work collaboratively with software engineering to deploy and operate systems. Additionally, this role will help automate and streamline operations and processes; as well as build and maintain tools for deployment, monitoring and operations, and troubleshoot and resolve issues in dev, test, and production environments. Primary Responsibilities: Supports software deployments, cloud infrastructure baselines, and operational availability of production systems. Managing, building, configuring, administering, operating and maintaining all components that comprise the DevOps environment. Defining enterprise Continuous Integration/Continuous Deployment processes and best practices Codifying DevOps best practices across the enterprise Developing and maintaining scripts to automate tool deployment to an AWS cloud environment and other tasks. <l

Leidos has an exciting opportunity for Cyber Security Engineer—Technical Lead in our Intel Security Sector's Analysis Solutions Business Area . Our talented team is at the forefront in Security Engineering, Computer Network Operations (CNO), Mission Software, Analytical Methods and Modeling, Signals Intelligence (SIGINT), and Cryptographic Key Management. At Leidos , we offer competitive benefits , including Paid Time Off, 11 paid Holidays, 401K with a 6% company match and immediate vesting, Flexible Schedules, Discounted Stock Purchase Plans, Technical Upskilling, Education and Training Support, Parental Paid Leave, and much more. Join us and make a difference in National Security! Job Summary This role is responsible for protecting the customer’s information systems and networks from potential cyber-attacks. The Cyber Security Engineer– Technical Lead will serve in a hands-on “player-coach&#34; capacity, dedicating approximately 75% of time to direct technical engineering, troubleshooting, and implementation work, while providing technical leadership and coordination across the security team. The candidate must display an excellent understanding of technology and utilization of Firewalls (Security Groups), VPNs, Data Loss Prevention (DPS), IDS/IPS, Web-Proxy, Security tools, and Security Audits. Candidate will work directly with Team leads, developers, operations personnel, and other Technical Leads throughout a DevSecOps life cycle both on policy and technical implementation of technologies. This is not a supervisory management role. Success in this position is measured by individual technical contribution and resolution of complex security issues, in addition to technical leadership impact. Primary Responsibilities: Plan, implement, manage, monitor, and upgrade security controls and tools used to protect enterprise systems and networks, while identifying opportunitie

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern deep learning — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as “the AI computing company.” We're looking to grow our company and establish teams with the most thoughtful people in the world. NVIDIA GH200 superchip provides performance and productivity required for strong scaling for HPC and generative AI workload. Scale out is inherent to design of this massive superchip. We are looking for expert engineers to come and help design rack level solutions for next generation scaling AI supercomputing platforms. We are looking for a strong technical architect to own end to end manageability architecture for these products in data centers. You will work with various component leads internally and externally, drive customer use cases, align architecture with customer requirements and release best products to market. Join us at the forefront of technological advancement. What you’ll be doing: Drive server management for large clusters and data centers deploying GPUs and Grace solution from Nvidia. Work with data center architects and cloud customers to narrow down on requirements for implementation to ensure speed of light product development. Work with internal teams to make sure requirements are designed and implemented in right way with each firmware and software module Collaborate with other leads to design & build data center health management workflow. Drive reliability and optimization in firmware architecture from a data center view point. Work closely with cluster bring up team and resolve is

About Graphcore Graphcore is a global leader in artificial intelligence computing systems. We design advanced semiconductors, software, and data center systems that provide the specialized processing power needed to advance AI while improving the efficiency required for broad adoption. As part of SoftBank Group, Graphcore belongs to a family of companies developing transformative technologies. Our U.S. engineering teams contribute to the hardware and software platforms that support the next generation of AI systems. The Opportunity We are looking for a recent graduate or early-career engineer to join the BMC Engineering team as a Graduate Firmware Engineer. You will develop low-level and embedded firmware that supports the operation, control, monitoring, and validation of advanced compute systems. You will work with experienced firmware, hardware, systems, and software engineers throughout the development lifecycle. The role combines hands-on implementation with automated testing, lab-based debugging, hardware bring-up, and analysis of interactions between firmware and the underlying platform. Start: September, 2027 Location: Austin, Texas, USA What You Will Do Design, implement, test, and maintain system and embedded firmware in C, C++, or Python. Take ownership of defined firmware features and deliver them from requirements and design through implementation, validation, and documentation. Develop and debug firmware in a Linux-based engineering environment using appropriate diagnostic tools and techniques. Create automated tests and scripts that improve firmware validation, test coverage, and engineering efficiency. Contribute to continuous integration and delivery workflows for firmware development and testing. Plan and conduct engineering experiments, analyze test data, and communicate findings clearly. Support lab setup, system configuration, hardware bring-up, and firmware validation on development platforms. Investigate firmware behavior and hardware-software

About us Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation. Job Summary We are seeking a Staff Hardware Engineer to provide advanced operational, diagnostic, and engineering support for Graphcore’s Arm-based hardware platforms across lab and data center environments. This role focuses on supporting hardware bring-up, validation, and troubleshooting of complex AI compute platforms, including server blades, racks, and rack-scale infrastructure. The successful candidate will collaborate closely with engineering, platform, and data center teams to ensure the reliability and performance of next-generation AI systems. The Team The Systems Engineering and Hardware Engineering teams are responsible for enabling the bring-up, validation, and operational reliability of Graphcore’s AI infrastructure platforms. The team works closely with server engineering, firmware teams, platform architects, and data center operations to support the development, testing, and deployment of next-generation AI compute systems. This collaborative environment enables rapid problem-solving and continuous improvement of Graphcore’s hardware platforms from early development through production deployment.

About us Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation. Job Summary We are seeking a Staff Hardware Engineer to provide advanced operational, diagnostic, and engineering support for Graphcore’s Arm-based hardware platforms across lab and data center environments. This role focuses on supporting hardware bring-up, validation, and troubleshooting of complex AI compute platforms, including server blades, racks, and rack-scale infrastructure. The successful candidate will collaborate closely with engineering, platform, and data center teams to ensure the reliability and performance of next-generation AI systems. The Team The Systems Engineering and Hardware Engineering teams are responsible for enabling the bring-up, validation, and operational reliability of Graphcore’s AI infrastructure platforms. The team works closely with server engineering, firmware teams, platform architects, and data center operations to support the development, testing, and deployment of next-generation AI compute systems. This collaborative environment enables rapid problem-solving and continuous improvement of Graphcore’s hardware platforms from early development through production deployment.

Hyliion is committed to creating innovative solutions that enable clean, flexible and affordable electricity production. The Company’s primary focus is to develop distributed power generators that can operate on various fuel sources to future-proof against an ever-changing energy economy. Job Purpose The Advanced Engineer, Power System Controls plays a key role in the design, development, and implementation of control software for Hyliion’s Karno Power Module. This position focuses on systems involving combustion, thermal management, pressure regulation, high-voltage, and power management. The engineer will be responsible for developing and validating control algorithms, tuning system parameters, and analyzing data to ensure performance meets engineering specifications. Additional responsibilities include preparing technical documentation, supporting root cause analysis, and ensuring timely, high-quality software delivery. The role requires cross-functional collaboration and occasional travel to support system testing and troubleshooting. Duties and Responsibilities Design, develop, and implement high-quality control software for Hyliion’s Karno Power Module, which includes combustion, thermal, pressure, high-voltage and power management systems. Define and conduct tests to verify software and tune control parameters to meet key performance indicators. Prepare reports and technical documentation related to system performance, control strategies, and compliance. Process and analyze data to verify software against engineering specifications, support root cause analysis and for optimizing performance. Ensure on time delivery with quality. Assist product team in defining customer requirements and generate corresponding engineering specifications. Qualifications Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. Qualifications include: Education, Experience and Cert

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. Tenstorrent is seeking talented Physical Design Engineers to implement high-performance blocks for our industry-leading CPU and AI/ML architectures. You'll own the complete implementation flow from synthesis to tapeout, working alongside world-class engineers to push the boundaries of performance, power, and area. If you're passionate about crafting silicon that powers the future of AI computing and thrive on solving complex design challenges, we want you on our team. This role is hybrid , based out of Austin, TX, Santa Clara, CA or Fort Collins, CO. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are A hands-on engineer with deep expertise in SOC/ASIC physical design and a track record of successful tapeouts. Passionate about optimizing PPA through innovative implementation techniques and close RTL collaboration. Strong problem solver who excels at debugging complex issues across design hierarchies. Collaborative team player who thrives in fast-paced, technically challenging environments. What We Need BS/MS/PhD in EE/ECE/CE/CS with proven experience in synthesis, PnR, and timing closure on taped-out designs. Expertise with industry-

About us Graphcore is one of the world’s leading innovators in artificial intelligence compute. We are developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and support the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of a family of companies responsible for some of the world’s most transformative technologies. Together, we share a bold vision to enable advanced artificial intelligence and ensure its benefits are accessible to everyone. Graphcore brings together AI researchers, silicon designers, software engineers and systems architects to solve complex technical challenges and deliver innovative computing solutions. Job Summary The Principal Electrical Engineer will be a technical authority within Data Center Engineering, leading the architecture and delivery of safe, resilient and scalable electrical infrastructure for high-density AI computing environments. Working with internal teams, data center developers, utilities, consultants and equipment partners, this role will guide projects from early technical studies through design, construction, commissioning, operation and lifecycle improvement. The successful candidate must reside in, or be willing to relocate to, Austin, Texas. Approximately 10% travel may be required. The Team The Data Center Engineering team is responsible for defining and enabling the infrastructure needed to deploy and operate Graphcore’s computing systems at scale. The team works across electrical, mechanical, thermal, controls, systems and operational disciplines, collaborating with external engineering and construction partners to deliver reliable, efficient and maintainable data center environments. Responsibilities and Duties Act as the technical authority for electrical engineering across data center infrastructure projects, from the utility or on-site power source through to the IT rack. Lead electrical archit

About us Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation. Job Summary We are seeking a Staff Hardware Engineer to provide advanced operational, diagnostic, and engineering support for Graphcore’s Arm-based hardware platforms across lab and data center environments. This role focuses on supporting hardware bring-up, validation, and troubleshooting of complex AI compute platforms, including server blades, racks, and rack-scale infrastructure. The successful candidate will collaborate closely with engineering, platform, and data center teams to ensure the reliability and performance of next-generation AI systems. The Team The Systems Engineering and Hardware Engineering teams are responsible for enabling the bring-up, validation, and operational reliability of Graphcore’s AI infrastructure platforms. The team works closely with server engineering, firmware teams, platform architects, and data center operations to support the development, testing, and deployment of next-generation AI compute systems. This collaborative environment enables rapid problem-solving and continuous improvement of Graphcore’s hardware platforms from early development through production deployment.