Develops rapid product prototypes and technology demonstrations in C/C++ and Python across evolving embedded hardware. Responsibilities include modifying drivers and software frameworks, designing architectures, establishing CI/CD and code review workflows, translating research algorithms into high-performance embedded code, supporting chip and board bring-up, collaborating with Systems and Physical AI teams, documenting implementations, and handing successful prototypes to production software teams.
About Lyte
Lyte builds perception systems for Physical AI operating in complex environments. The company combines custom silicon, integrated sensors, and software into a unified platform for robotics, mobility, and next-generation automation. Lyte is headquartered in Sunnyvale, California, with a global presence. For more information, visit www.lyte.ai
If you’re excited about building impactful technology in a dynamic, hands-on environment, we’d love to hear from you!
About the role
- We are seeking a highly efficient and motivated software engineer to help us prototype new products, components, and systems. These prototypes will be used to validate new technologies and help deliver technology demos based on existing products. The candidate should be able to work in close collaboration with the Systems and Physical AI organizations and deliver on functionality milestones within days or weeks of project initiation. The candidate must have expert-level proficiency in C/C++ and Python, including in resource-constrained embedded environments. The candidate should also have strong understanding of computer architectures used in modern embedded systems.
We value diverse technical backgrounds; the ideal candidate might come from a mix of high-growth industry roles and deep-tech academic research, provided they can demonstrate a transition toward fast-paced product delivery.
What you'll do
- Develop software in C++ and Python over evolving hardware, i.e., software development simultaneously with and over chip bring-up, board design, and ongoing hardware development more generally
- Build upon existing drivers and established software frameworks, including working directly with source code and modules developed and owned by other employees
- Extensively modify existing components, including mature components to achieve new functionality – potentially working on the side of the existing codebase
- Establish streamlined, risk-based code review and CI/CD workflows tailored for rapid iteration without compromising system stability.
- Formulate and implement software architectures on short timescales
- Succeed in a cross-functional environment with key stakeholders outside of the software organization, including Systems and Physical AI organizations
- Technical ownership and long-term support of the developed prototypes well into the production process
- Hand-off successful prototypes to the production software teams
- Act as the primary bridge between theoretical research and physical implementation, re-architecting algorithms from subject matter experts (e.g., PhD researchers or Systems Engineers) into high-performance embedded code.
- Synthesize complex technical concepts into 'living' documentation and modular code that accelerates the production roadmap.
- Leverage AI-assisted coding and simulation tools to accelerate boilerplate generation and early-stage validation.
Required Qualifications
- Bachelor's degree in Computer Science, Electrical Engineering, Applied Mathematics, or other related technical field
- 2+ years of professional industry experience, or 5+ years of high-impact applied research (e.g., PhD/Post-Doc) with a demonstrable focus on tangible hardware-software integration.
- Advanced proficiency in Python
- Advanced proficiency in C/C++
- Proven experience in rapid prototyping
- Proven experience in working with cross-functional teams
- Strong written and verbal communication skills
Preferred Qualifications
- MS or PhD in Computer Science, Electrical Engineering, Applied Mathematics, or other related technical field
- 5+ years of formal employment experience developing software in embedded systems
- Engineering background in EE, systems, optics, or laser-based sensing
- Ability to operate effectively in a startup environment with ambiguity, speed, and strong ownership culture
- Proven experience in software development for embedded Linux
- Proven experience in chip and board bring-up
- Experience with real-time operating systems (RTOS)
- Experience with hardware debugging tools such as logic analyzers, oscilloscopes, and JTAG/SWD debuggers.
- Familiarity with interpreting hardware schematics and datasheets to inform software architecture.
- Proven track record of translating complex academic or R&D concepts (e.g., from a thesis or research project) into functional, real-world prototypes.
- Experience with Hardware-in-the-Loop (HIL) testing and automated firmware validation frameworks.
- Familiarity with quantizing and deploying machine learning models to resource-constrained edge devices.
Benefits (subject to location and local regulations)
- Competitive salary and equity
- Comprehensive medical, dental, and vision coverage
- 401(k) retirement plan
- Flexible vacation and time-off policy
- Collaborative, fast-paced, and inclusive work environment
- Opportunity to work on cutting-edge technologies with a highly cross-functional team
Similar Jobs
Artificial Intelligence • Software
Own the full enterprise sales cycle for Fieldguide’s Internal Audit AI platform, targeting Fortune 1000 and large corporate accounts. Build executive and cross-functional relationships, conduct consultative discovery, deliver solution walkthroughs, develop account and territory plans, manage MEDDICC sales processes, maintain CRM accuracy and forecasts, and exceed revenue targets. The role involves complex, multithreaded deals and up to 30% regional and national travel.
Top Skills:
AICRM
Artificial Intelligence • Cloud • Sales • Security • Software • Cybersecurity • Data Privacy
Lead enterprise-scale service mesh implementation across AWS EKS clusters and hundreds of microservices. Establish Kubernetes standards, operate production infrastructure, improve GitOps and CI/CD automation, support PCI DSS compliance, mentor engineers, and drive reliability, observability, capacity planning, incident response, and global platform architecture for a 24/7 SaaS environment.
Top Skills:
Amazon EksAWSAws App MeshCi/CdGitopsGoGrafanaHelmIstioKubernetesLinkerdLinuxMtlsNetwork PoliciesOpensearchPci DssPod Security StandardsPrometheusPythonRbacTerraform
Artificial Intelligence • Cloud • Sales • Security • Software • Cybersecurity • Data Privacy
Manage post-acquisition integration programs and workstreams within SailPoint’s Integration Management Office. Responsibilities include creating integration plans, tracking milestones, dependencies, RAID logs, and TSA deliverables; coordinating cross-functional teams; supporting due diligence and Day 1 readiness; preparing executive status reports; improving integration playbooks; and leading complex integrations while managing budgets, risks, and synergies.
Top Skills:
ConfluenceJIRAMicrosoft ProjectSlack
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine


