Systems engineer jobs in Cupertino, CA

Maxonic maintains a close and long-term relationship with our direct client. In support of their needs, we are looking for: Job Title: Senior Linux Systems Administrator Job Type: Fulltime Work Schedule: Onsite 5 days a week As a Senior Systems Administrator, you will work with talented colleagues on challenging projects within the IT Infrastructure. You'll bring a proactive approach to server infrastructure management and support, addressing both immediate operational requirements and long-term systems stability. Responsibilities Implement, and maintain various Linux (Red Hat, CentOS, Ubuntu, etc.) server infrastructures (physical and virtual), focusing on scalability, reliability, and security. Perform systems maintenance and system upgrades including service packs, patches, hot fixes, and security configurations. Monitor server performance, ensure system availability and reliability, and provide optimization recommendations. Troubleshoot server infrastructure problems, outages, and ensure rapid resolution of system incidents. Work with the latest compute and storage management tools Establish & maintain a strong relationship with the business including local, remote, and regional users regarding server technology solutions. Document server configuration and operational procedures. Establish & maintain healthy working relationships with all technology departments Be viewed as a knowledgeable and reliable technical resource across all infrastructure technologies. Ensure the business understands our service portfolio by translating technical solutions into simple to understandable dialogue Manage and support Public Clouds associated security, compute and storage services like virtual machines, kubernetes, db, storage, etc. Partner with the InfoSec team to ensure Security best practices are enforced in an effective and scalable manner. Qualifications: 3+ years of hands-on experience with Linux administration and application resource utilization monitoring. 3+ years of experience in systems administration with a strong focus on Linux environments. Proficiency in shell scripting and automation tools (e.g., Ansible, Puppet, Chef). Experience with virtualization technologies (e.g., VMware, KVM). Solid understanding of networking concepts (TCP/IP, DNS, DHCP, firewalls). Familiarity with monitoring tools (e.g., Nagios, Zabbix, Prometheus). Experience with cloud platforms (AWS, Azure, GCP) is a plus. Strong problem-solving and analytical skills. Excellent communication and documentation abilities. Minimum 4-year college degree in Management Information Systems, Computer Science, or equivalent discipline. Linux Certification a plus. Cloud Certification a plus. About Maxonic: Since 2002 Maxonic has been at the forefront of connecting candidate strengths to client challenges. Our award winning, dedicated team of recruiting professionals are specialized by technology, are great listeners, and will seek to find a position that meets the long-term career needs of our candidates. We take pride in the over 10,000 candidates that we have placed, and the repeat business that we earn from our satisfied clients. Interested in Applying? We'd love to hear from you! Please click apply with your most current resume and anything else you'd like us to know about you - commute preferences, desired work environments, etc. You should also feel free to call Saurav at ************ or email me at ******************

Network Administrator (AWS + On-Prem Hybrid Infrastructure) $130,000 - $160,000 Full-time | On-site Our client designs, builds, and operates advanced small satellite systems that power end-to-end space missions for communications, Earth observation, and scientific exploration. Their technology combines space-based innovation with secure, scalable ground systems, enabling seamless integration between orbit and operations on Earth. Position Summary We are seeking an experienced Network Administrator with a strong background in managing hybrid cloud and on-premises environments. The ideal candidate has hands-on expertise with AWS infrastructure, Cisco Firepower (FTD 1010) firewalls, and virtualized systems. In this role, you'll ensure reliable, secure, and high-performance connectivity between physical sites and AWS-hosted systems that support mission-critical satellite operations. This role involves maintaining and improving our secure network connectivity between physical sites and AWS-hosted infrastructure, ensuring uptime, security, and smooth operation across mission-critical systems that support our satellite operations and internal teams. Key Responsibilities Administer and maintain AWS infrastructure, including EC2 instances, VPCs, Route53, and AWS VPN configurations Manage AWS Veeam backup systems for EC2 and virtual machine snapshots, ensuring regular and on-demand backups Configure and maintain Cisco FTD 1010 firewalls, including site-to-site VPNs linking AWS and remote offices Monitor and troubleshoot VPN and network connectivity for users, infrastructure, and remote systems Support on-premises networking equipment, including routers, switches, and Wi-Fi systems (e.g., UniFi UDM SE) Maintain and manage VMware ESXi servers hosting internal VMs, GitLab runners, and development resources Administer OpenVPN servers, renew certificates, and manage user access using automation scripts Manage DNS configurations via AWS Route53 for hosted zones and internal systems Implement and maintain network security policies and consistent backup procedures across environments Diagnose and resolve routing, NAT, and performance issues across hybrid networks Collaborate with DevOps, IT, and engineering teams to support infrastructure scaling and modernization Minimum Qualifications Bachelor's degree in Information Technology, Computer Engineering, or related field, or equivalent hands-on experience 3+ years of experience as a Network Administrator or Systems Administrator in hybrid environments Proficiency in AWS infrastructure (EC2, VPC, Route53, VPN, IAM) Experience with Cisco Firepower Threat Defense (FTD 1010) or similar firewall platforms Strong understanding of VPNs, routing, NAT, and tunneling protocols Experience managing Veeam Backup for AWS or equivalent tools Familiarity with VMware ESXi environments and virtual machine management Proficiency in Linux administration (Ubuntu preferred) and SSH key management Hands-on experience configuring OpenVPN servers and scripting user management tasks Strong documentation, organization, and problem-solving skills Preferred Qualifications Experience with AWS GovCloud, GitLab infrastructure, or similar DevOps platforms Familiarity with UniFi network management or Raspberry Pi remote nodes Working knowledge of physical security systems (e.g., keyfob access, ADT) AWS or Cisco certifications (Solutions Architect, SysOps, CCNA, or higher) Why Join This Team? Work at the intersection of cloud and on-prem infrastructure supporting real-world satellite missions Own critical network systems that bridge space and terrestrial operations Collaborate with a small, high-performing engineering team where your work has a direct impact Grow into advanced roles in CloudOps, Infrastructure Engineering, or DevSecOps as the organization scales

Systems Engineer - Video Intelligence Infrastructure - San Francisco About the Company A Series A Funded start-up who already have millions in recurring revenue are building next-generation AI infrastructure for video intelligence are looking for a Systems Engineer to join their team. What You'll Be Doing: Design and engineer systems that handle compute, scheduling, and orchestration of complex ML + ETL pipelines Optimize hyper-fast distributed systems running at the scale of thousands of GPUs Build systems that process video data quickly, reliably, and cost-effectively at internet scale Develop robust internal tooling and CI/CD pipelines for rapid ML team iteration Focus on system uptime and performance optimization for mission-critical infrastructure What We're Looking For: 3+ years building foundational data infrastructure Experience designing and maintaining pipelines that process petabytes of data Strong background developing CI/CD pipelines for ML-focused teams Excellent coding skills in Go and Python Independent contributor who leads by example What's In It For You Competitive salary up to $250k Small, high-impact team with significant growth trajectory Opportunity to work with top AI video labs and collect world-class datasets Apply now for immediate consideration!

Job Title: HIL Test Engineer (BMS System) Employment Type: Full-Time We are seeking a skilled Embedded Engineer with strong expertise in Hardware-in-the-Loop (HIL) testing and Battery Management Systems (BMS). The ideal candidate will be responsible for developing, validating, and optimizing embedded control systems related to automotive or industrial battery applications. This role involves hands-on work with HIL platforms, embedded firmware, diagnostics, and battery system integration. Key Responsibilities: Develop, validate, and troubleshoot embedded software for Battery Management Systems (BMS). Plan, execute, and automate HIL test cases using tools such as dSPACE, NI, Vector, or equivalent systems. Create test scripts, perform fault injection, and ensure BMS compliance with safety and performance requirements. Analyze system behavior, debug issues, and implement corrective actions across embedded software and hardware. Work closely with cross-functional teams including systems engineering, hardware, validation, and controls. Support integration testing for HV battery packs, modules, and EV subsystems. Develop test documentation: test plans, procedures, reports, and traceability matrices. Perform CAN/LIN communication analysis using tools such as CANoe, CANalyzer, or Vector tools. Contribute to continuous improvement of testing frameworks, automation, and embedded processes. Required Qualifications: Bachelor's or Master's degree in Electrical Engineering, Embedded Systems, Electronics, Mechatronics, or related field. 3-6+ years of experience in embedded systems development and/or validation. Hands-on experience with HIL testing (dSPACE, NI, Vector VT, ETAS LABCAR, etc.). Strong understanding of Battery Management Systems, SOC/SOH estimation, cell balancing, thermal management, and HV safety. Proficiency in embedded C/C++, control algorithms, and microcontroller-based systems. Experience with CAN communication, UDS diagnostics, and scripting languages (Python, CAPL, MATLAB/Simulink). Preferred Qualifications: Experience with EV powertrain, high-voltage batteries, or automotive functional safety (ISO 26262). Familiarity with real-time operating systems (RTOS) and AUTOSAR environments. Knowledge of automation frameworks and CI/CD for embedded testing. Experience working with model-based development (MBD).

Source One is a consulting services company and we're currently looking for the following individual to work as an on-site consultant to an autonomous vehicle (AV) ride-sharing company in Hayward, CA. Title: SAP Operation Support Engineer (Contract) Pay Rate: $87.25/hr (W-2) Summary: Our client is seeking an SAP Operation Support Engineer to support SAP S/4, key Base Operations systems, and broader IT infrastructure initiatives. This role focuses on SAP data accuracy, system configuration, operational improvements, and cross-functional collaboration to enhance vehicle and production operations. You will also assist with analytics tools, documentation systems, and general IT application support. The ideal candidate is detail-oriented, proactive, and experienced in SAP S/4 and system operations, with strong communication skills and the ability to manage complex data and processes in a fast-paced environment. Key Responsibilities : SAP Support & Data Management - Serve as the SAP data steward: maintain vehicle lists, equipment structures, work centers, measuring points, counters, task lists, maintenance plans, and catalog codes. - Partner with the Business Applications team on As-Maintained BOM cleanup and resolving data inaccuracies. - Provide configuration management support in SAP for Base Operations ahead of key milestones. - Lead SAP improvement and automation initiatives and evaluate user experience to drive usability enhancements. - Act as the primary SAP subject-matter expert, handling troubleshooting, maintenance, and user support. - Work with internal training teams to create module-specific SAP training for BaseOps users. Systems, Infrastructure & IT Application Support - Provide general IT application support for Base Operations systems and advocate operational needs with Corporate IT. - Lead IT infrastructure and application improvement projects informed by data insights and user feedback. - Support development, maintenance, and operations of technical publications tools, release software, and customer-facing documentation systems. - Improve documentation review workflows in partnership with the BaseOps documentation team. - Support development and use of analytics tools, dashboards, and reporting frameworks to improve operational efficiency. - Conduct data auditing and compliance activities to ensure accuracy, governance, and system reliability. - Communicate project progress, milestones, and outcomes to internal and external partners. Daily Focus : - Manage SAP data accuracy and system improvement projects in close collaboration with Business Applications, Program Management, Strategic Operations, Data Science, Fleet Support, and Engineering. - Monitor and support BaseOps systems and infrastructure, lead software/hardware rollouts, deliver training, troubleshoot issues, and contribute to overall system architecture. - Provide support for SAP S/4, SAP MES, and other IT systems; contribute to operational tools and processes that improve fleet and production uptime. - As needed, support website development and maintenance of operational databases and dashboards. Qualifications : - B.S. in Information Technology or an equivalent engineering field - 6-8 years of experience in a System Operations Support role - Hands-on experience with SAP S/4 - Strong written and verbal communication skills - Highly self-motivated, detail-oriented, and able to prioritize multiple assignments - Experience with UI development/maintenance and UX studies - Coding experience: HTML, CSS, JavaScript Bonus Qualifications : - Experience with SAP ME/MII - Familiarity with Jira/Confluence or similar tools - Experience with web development tools (e.g., Oxygen) and building analytics dashboards - Prior support experience in production or vehicle fleet environments

We are actively searching for a Distributed Systems Engineer to join our team on a permanent basis. In this founding engineer role you will focus on building next-generation data infrastructure for our AI platform. If you have a passion for distributed systems, unified storage, orchestration, and retrieval for AI workloads we would love to speak with you. Our office is located in downtown SF and we collaborate two days a week onsite. Your Rhythm: Design, build, and maintain data infrastructure systems such as distributed compute, data orchestration, distributed storage, streaming infrastructure, machine learning infrastructure while ensuring scalability, reliability, and security Ensure our data platform can scale by orders of magnitude while remaining reliable and efficient Tackle complex challenges in distributed systems, databases, and AI infrastructure Collaborate with technical leadership to define and refine the product roadmap Write high-quality, well-tested, and maintainable code Contribute to the open-source community and engage with developers in the space Your Vibe: 3+ years of professional distributed database systems experience Expertise in building and operating scalable, reliable and secure database infrastructure systems Strong knowledge around distributed compute, data orchestration, distributed storage, streaming infrastructure Strong knowledge of SQL and NoSQL databases, such as MySQL, Postgres, and MongoDB. Programming skills in Python Passion for building developer tools and scalable infrastructure Available to collaborate onsite 2 days a week Our Vibe: Relaxed work environment 100% paid top of the line health care benefits Full ownership, no micro management Strong equity package 401K Unlimited vacation An actual work/life balance, we aren't trying to run you into the ground. We have families and enjoy life too!

Staff / Lead ML Infrastructure Engineer San Francisco, CA - Onsite Salary - Over market average + equity We are building one of the world's leading generative video and multimodal AI platforms, and we're looking for a senior infrastructure engineer to drive the backbone that makes it possible. This role is ideal for an engineer from a top-tier tech company who has built cloud-scale systems, high-performance compute platforms, and battle-tested CI/CD pipelines that support complex ML workloads. What You'll Own Core ML Platform Architecture: Design and evolve the infrastructure that supports large-scale generative video and multimodal model training, evaluation, and deployment. High-Throughput Compute Systems: Build and optimize GPU/TPU clusters, distributed training systems, and orchestration layers tailored for video-heavy pipelines. Production Reliability for Generative Models: Create the tooling and services needed to safely push frequent model updates while handling massive compute loads and long-running jobs. End-to-End CI/CD for ML: Lead the development of automated pipelines for model training, validation, artifact management, and production rollout. Multimodal Data Infrastructure: Build systems to ingest, version, transform, and serve large-scale video, audio, and text datasets with high reliability. Internal Developer Experience: Partner with research, product, and applied ML teams to build intuitive internal tooling for experiment tracking, model lineage, and resource scheduling. Technical Leadership: Mentor engineers, set platform standards, and influence long-term architectural direction. What You've Done Experience architecting and operating large-scale infrastructure at a cloud provider, hyperscaler, or leading AI company. Built or owned mission-critical CI/CD systems, high-capacity compute platforms, or data infrastructure supporting ML teams. Deep experience with distributed compute across GPUs/accelerators, Kubernetes, and cloud infrastructure (AWS/GCP/Azure). Strong engineering fundamentals in Python, Go, or equivalent languages. Previous exposure to ML training pipelines-especially systems that handle heavy video, multimodal, or high-dimensional data. Demonstrated ability to lead complex cross-org initiatives and drive technical strategy. Nice to Have Experience with video processing systems, large-scale media pipelines, or streaming architectures. Familiarity with modern multimodal or video-generation frameworks (PyTorch, JAX, diffusers, custom accelerators). Experience with Ray, Triton, CUDA optimization, or specialized scheduling for ML workloads. Background working in high-growth AI startups or research-focused environments. Security and compliance considerations for models that generate or process user content. Why Join Shape the underlying platform powering one of the most advanced generative video systems in the world. Influence the future of multimodal AI by building infrastructure that directly accelerates research and product breakthroughs. Work closely with experienced founding engineers, researchers, and platform builders from leading tech companies. Highly competitive compensation, meaningful equity, and strong in-person engineering culture in San Francisco.

2-7 years of experience in software testing. Strong understanding of STLC, SDLC, and defect lifecycle. Camera Testing experience is mandatory. Good communication and problem-solving skills.

We are seeking highly skilled OpenStack and Nutanix Administrators to join our IT Infrastructure team. This role is crucial in managing, optimizing, and ensuring the seamless operation of cloud and hyper-converged infrastructure environments. The ideal candidates will possess strong technical expertise, excellent problem-solving skills, and a proven ability to work in dynamic environments. Key Responsibilities - Deploy, configure, and maintain OpenStack cloud environments and Nutanix hyper-converged infrastructure. - Monitor system performance, troubleshoot issues, and ensure high availability of services. - Design and implement scalable solutions to meet organizational needs. - Collaborate with cross-functional teams to align infrastructure with business objectives. - Perform upgrades, patches, and routine maintenance for OpenStack and Nutanix systems. - Develop automation scripts for efficient system management using tools like Ansible, Terraform and Pulumi. - Ensure compliance with security standards and implement best practices for data protection. - Document processes, configurations, and troubleshooting steps for knowledge sharing. Qualifications - Bachelors in Computer Science (or related field) and 6 - 9 years of relevant experience. - Strong expertise in OpenStack architecture, deployment, and management. - Hands-on experience with Nutanix AHV, Prism Central, and related tools. - Proficiency in Linux system administration and scripting (e.g., Bash, Python). - Excellent familiarity with virtualization technologies (e.g., KVM) and container platforms (e.g., Kubernetes). - Knowledge of networking concepts such as VLANs, SDN, and load balancing. - Experience with monitoring tools like Prometheus or Nagios. - Excellent communication skills to collaborate with technical and non-technical stakeholders. - Certifications in OpenStack or Nutanix (e.g., NCP-MCI) are a plus.

San Francisco, CA (Onsite) About the Company A fast-moving AI research group is building the core video data infrastructure used by leading AI labs and major tech companies. The team is small at around fifteen people, nearly all engineers, and recently pivoted to focus exclusively on high-quality video data at massive scale. The shift has driven significant revenue growth, and they are now planning to expand the team steadily over the next few months. The culture is straightforward: engineering led, product focused, low ego, and built around people who enjoy ownership. They work in person five days a week in their San Francisco office, moving quickly, solving hard problems, and avoiding micromanagement. The Role This position focuses on designing and scaling distributed systems that support huge ML and ETL workloads across petabytes of video. You will own core infrastructure: compute scheduling, orchestration, throughput, reliability, cost efficiency, and the internal tooling that keeps the entire engineering group moving at pace. The company is beginning to scale its infrastructure footprint aggressively, and this role will become central to that growth. It is a hands-on IC position suited to someone who has operated critical systems before and wants to shape the foundation of a rapidly expanding platform. What You'll Work On • Architect and scale distributed systems for large-scale ML and ETL workloads • Build compute orchestration and scheduling across thousands of GPUs • Improve uptime, resilience, and execution speed of high-volume data pipelines • Design pipelines capable of handling petabyte-level video datasets • Lead the development of CI/CD and internal tooling for fast iteration • Partner closely with research engineers delivering new video models and algorithms • Operate in a high-trust environment with strong autonomy and clear ownership Requirements • 3+ years building foundational distributed systems or data infrastructure • Experience running critical systems at significant scale • Proficient across cloud architectures • Strong coding experience with Go (preferred) and Python • Background building or maintaining large-scale pipelines • Experience with ML-focused CI/CD and automation • Video domain experience is not required • Operates as a strong IC who leads through action • Fully onsite in San Francisco, Monday to Friday Culture Fit • Enjoys ambiguity, problem discovery, and self-direction • Communicates clearly and concisely • Shows strong intellectual curiosity • Low ego, collaborative mindset • Motivated by building core systems in a small, high-caliber team Red flags include weak communication, low curiosity, or unclear motivation for the domain. Interview Process Intro call focused on culture, curiosity, and communication Technical discussion on background and complexity of past work Problem-solving session with a research engineer Onsite research problem and collaboration exercise

🚀 Hiring: Infrastructure Engineer | SF (Onsite Only) Chalk is building the data platform powering next-gen machine learning applications - eliminating the complexity and scale issues that hold teams back. Backed by a recent $50M Series A, we're growing fast and looking for an exceptional Infrastructure/Platform Engineer to join us onsite in San Francisco. What you'll do: • Build automation + orchestration for Chalk's ML data platform • Develop infra tooling across AWS/GCP using Python, Go, Terraform • Own deployments both in our hosted platform and customer cloud environments • Work across Compilers, DBMS, and distributed systems challenges • Contribute as an early engineer with high autonomy and impact What we're looking for: • 2+ years in infra engineering • Strong experience coding for infra automation • Python, Go, or Terraform proficiency • AWS or GCP hands-on experience • Strong collaboration skills - bonus if you've worked with customers or Sales teams Why Chalk? • High-growth startup, massive ownership • Competitive salary + generous equity • Fully stocked office, daily meals, strong benefits • 15 PTO days + 15 company holidays 🎄 • In-office culture (Mon-Fri) If you're excited about building the backbone of ML-driven systems at scale, let's talk! 🚀

RTL Engineer Fulltime We are urgently seeking experienced RTL Engineers to join our team. The selected candidates will be responsible for developing and executing verification plans, building robust verification environments, and collaborating closely with design teams to ensure high-quality deliverables. Responsibilities Plan: Develop comprehensive Core Verification Plans based on micro-architecture and design specifications. Develop: Architect and implement reusable, scalable verification environments using System Verilog/UVM. Test: Create and run constrained-random and directed tests to achieve high functional and code coverage. Debug: Analyze simulation results, root-cause complex failures, and work with design teams to resolve issues. Automate: Build and maintain automation scripts (Python/Perl) to enhance verification workflows and regression management. Requirements Mandatory expertise in System Verilog and UVM. Minimum 7 years of hands-on verification experience. Strong understanding of digital logic design and verification methodologies. Experience verifying digital systems using standard IP components/interconnects (e.g., microprocessor cores, hierarchical memory subsystems). Ability to work independently and provide technical feedback to FE RTL design teams and CPU/IP micro-architects. Proficiency with industry-standard EDA simulation and debug tools. Strong debugging and root-cause analysis skills. Scripting experience (Python, Perl). Excellent written and verbal communication skills in English. Added keywords for additional candidates. HBM Memory Controller SoC DRAM TPU ARM Cortex ARM M7 There are three core expectations: Strong, independent leads Engineers who can operate with confidence, reduce dependency on the client's thin internal team, and take real ownership of blocks. Consistency and continuity We cannot afford churn - selected leads must be stable, reliable long-term contributors. Ability to scale with the program Additional phases may spin up quickly; leads should be capable of mentoring and guiding expansion teams. Thanks and Regards, Manisha Dabral Signature IT World Inc. *********************

We have below Following Contract Positions Available If you have profiles please share me at ****************************** Job Title: IT Google Workspace Engineer Duration Contract Skillset Requirements for the Role: IT Google Workspace Engineer - BS/MS degree in computer science, engineering, or a related subject, or equivalent experience. - Proven experience in a systems engineer or similar role, with a strong background in IT infrastructure and support. - Deep, hands-on experience administering Google Workspace (formerly G Suite) at an enterprise level. - Managed or led the full lifecycle of Microsoft 365 to Google Workspace migrations, including data transfer, user provisioning, and post-migration support. - Demonstrable experience using ITSM tools, with a strong preference for ServiceNow. - Fundamental understanding of information security principles and experience working collaboratively with security teams. - Solid scripting skills (e.g., Javascript, Python, GAM) to automate tasks and improve efficiency. - Excellent communication skills, able to articulate technical issues to both technical and non-technical audiences and work effectively across teams. - Highly self-motivated, AI evangelist, possessing an energetic disposition and a positive attitude geared toward data-driven decisions and high-impact outcomes. - Plays a key role in maintaining service level agreements, applying formal change management procedures to minimize risk and disruption, and leading incident response efforts. - Capable of independently driving initiatives forward, defining requirements, building project plans, and managing resources to deliver successful outcomes. - Continuously embraces emerging technologies, including AI-powered tools, to enhance service delivery, drive automation, and stay adaptive in a fast-evolving IT landscape. Share me resumes at ******************************

Job Title: Computer Vision Engineer V - Imaging Simulation Engineer Duration: 12 Months (Extension Possible) Rate: $127/hr, W2 Benefits: Medical, Dental, Vision and Weekly Pay Role Summary Client Reality Labs is a leader in designing virtual and augmented reality systems. This role supports the Cameras Architecture Team as an Imaging Simulation Engineer, responsible for developing, validating, and executing end-to-end camera system simulations-including optics, sensors, algorithms, and software pipelines-to impact future camera architectures. The position collaborates with researchers, imaging scientists, algorithm engineers, optics teams, and camera architects to enable high-fidelity simulations and accelerate camera technology development for next-generation AR/VR products. Key Responsibilities Develop, validate, and execute state-of-the-art imaging simulation software tools to support Client camera hardware exploration, ML dataset generation, and product architecture studies. Investigate simulation methods such as ISET, ZEMAX, and non-sequential ray tracing to model realistic camera behavior. Experiment and data collection to validate simulator accuracy and to improve simulator modeling capability and efficiency Build and bring up lab setups for image data acquisition of camera prototypes to support camera design studies. Operate, calibrate, and perform routine maintenance of lab equipment. Develop and document camera test methodologies to support 2D/3D camera system performance analysis. Develop and debug test scripts for image data collection automation Processing, analysis and organizing measurement data; presentation of initial analysis Drive supplier interaction and management to deliver camera prototypes in support of concept demonstrations Qualifications:(10+ Years) Minimum Qualifications: Advanced degree (M.S.) or equivalent acquired experience in a discipline such as Imaging Science, Image Processing, Computer Vision, or related fields Knowledge of image formation process (spectrum, optics/aberrations, PSF, sensor noise, Fourier theory, sampling/aliasing) needed to successfully model and simulate complex imaging phenomena Experience and knowledge in developing and tuning Image Signal Processing (ISP) algorithms and pipeline. Experience coding in languages such as MATLAB, Python, C/C++, preferably CUDA, design code for efficiency, and target different platforms such as GPU, Cloud, and other Experiences in image quality testing of camera systems and familiar with image quality metrics and analysis • Hands on experience in the development of lab setups for camera system performance study Experiences in camera calibration and modeling of imaging systems Familiar with image sensor, imaging optics, and image processing algorithms Ability to work with minimal direction and managing a project independently from start to finish Must Have Skills: Understanding of image formation, capturing, and processing pipeline and techniques Python/Matlab programming, shell scripting skills Understanding of subjective and objective image quality evaluation metric and testing procedure Nice-to-Have Skills Hands-on experience developing lab setups for camera system studies. Experience with camera calibration and modeling. Experience at top-tier imaging companies. Degrees / Certifications Required: Bachelor's degree required. Master's or PhD preferred. Interview Process Minimum 2 rounds: Initial hiring manager screen Technical interview with the engineering team Topics: imaging simulation, ISP pipelines, image formation, camera modeling, past project deep dives. Timing: Manager screen: 30 minutes Technical interview: 1 hour Pursuant to the California Fair Chance Act, Los Angeles County Fair Chance Ordinance, Los Angeles Fair Chance Initiative for Hiring Ordinance, and San Francisco Fair Chance Ordinance, qualified applicants will be considered for assignment with arrest and conviction records. Criminal history may have a direct, adverse, and negative relationship with some job duties such as adhering to company policies, exercising sound judgment, managing stress, working respectfully with others, meeting client expectations, and safeguarding business operations and reputation. #TMN

Systems Engineer - Video Intelligence Infrastructure - San Francisco About the Company A Series A Funded start-up who already have millions in recurring revenue are building next-generation AI infrastructure for video intelligence are looking for a Systems Engineer to join their team. What You'll Be Doing: Design and engineer systems that handle compute, scheduling, and orchestration of complex ML + ETL pipelines Optimize hyper-fast distributed systems running at the scale of thousands of GPUs Build systems that process video data quickly, reliably, and cost-effectively at internet scale Develop robust internal tooling and CI/CD pipelines for rapid ML team iteration Focus on system uptime and performance optimization for mission-critical infrastructure What We're Looking For: 3+ years building foundational data infrastructure Experience designing and maintaining pipelines that process petabytes of data Strong background developing CI/CD pipelines for ML-focused teams Excellent coding skills in Go and Python Independent contributor who leads by example What's In It For You Competitive salary up to $250k Small, high-impact team with significant growth trajectory Opportunity to work with top AI video labs and collect world-class datasets Apply now for immediate consideration!

Staff / Lead ML Infrastructure Engineer San Francisco, CA - Onsite Salary - Over market average + equity We are building one of the world's leading generative video and multimodal AI platforms, and we're looking for a senior infrastructure engineer to drive the backbone that makes it possible. This role is ideal for an engineer from a top-tier tech company who has built cloud-scale systems, high-performance compute platforms, and battle-tested CI/CD pipelines that support complex ML workloads. What You'll Own Core ML Platform Architecture: Design and evolve the infrastructure that supports large-scale generative video and multimodal model training, evaluation, and deployment. High-Throughput Compute Systems: Build and optimize GPU/TPU clusters, distributed training systems, and orchestration layers tailored for video-heavy pipelines. Production Reliability for Generative Models: Create the tooling and services needed to safely push frequent model updates while handling massive compute loads and long-running jobs. End-to-End CI/CD for ML: Lead the development of automated pipelines for model training, validation, artifact management, and production rollout. Multimodal Data Infrastructure: Build systems to ingest, version, transform, and serve large-scale video, audio, and text datasets with high reliability. Internal Developer Experience: Partner with research, product, and applied ML teams to build intuitive internal tooling for experiment tracking, model lineage, and resource scheduling. Technical Leadership: Mentor engineers, set platform standards, and influence long-term architectural direction. What You've Done Experience architecting and operating large-scale infrastructure at a cloud provider, hyperscaler, or leading AI company. Built or owned mission-critical CI/CD systems, high-capacity compute platforms, or data infrastructure supporting ML teams. Deep experience with distributed compute across GPUs/accelerators, Kubernetes, and cloud infrastructure (AWS/GCP/Azure). Strong engineering fundamentals in Python, Go, or equivalent languages. Previous exposure to ML training pipelines-especially systems that handle heavy video, multimodal, or high-dimensional data. Demonstrated ability to lead complex cross-org initiatives and drive technical strategy. Nice to Have Experience with video processing systems, large-scale media pipelines, or streaming architectures. Familiarity with modern multimodal or video-generation frameworks (PyTorch, JAX, diffusers, custom accelerators). Experience with Ray, Triton, CUDA optimization, or specialized scheduling for ML workloads. Background working in high-growth AI startups or research-focused environments. Security and compliance considerations for models that generate or process user content. Why Join Shape the underlying platform powering one of the most advanced generative video systems in the world. Influence the future of multimodal AI by building infrastructure that directly accelerates research and product breakthroughs. Work closely with experienced founding engineers, researchers, and platform builders from leading tech companies. Highly competitive compensation, meaningful equity, and strong in-person engineering culture in San Francisco.

We are actively searching for a Distributed Systems Engineer to join our team on a permanent basis. In this founding engineer role you will focus on building next-generation data infrastructure for our AI platform. If you have a passion for distributed systems, unified storage, orchestration, and retrieval for AI workloads we would love to speak with you. Our office is located in downtown SF and we collaborate two days a week onsite. Your Rhythm: Design, build, and maintain data infrastructure systems such as distributed compute, data orchestration, distributed storage, streaming infrastructure, machine learning infrastructure while ensuring scalability, reliability, and security Ensure our data platform can scale by orders of magnitude while remaining reliable and efficient Tackle complex challenges in distributed systems, databases, and AI infrastructure Collaborate with technical leadership to define and refine the product roadmap Write high-quality, well-tested, and maintainable code Contribute to the open-source community and engage with developers in the space Your Vibe: 3+ years of professional distributed database systems experience Expertise in building and operating scalable, reliable and secure database infrastructure systems Strong knowledge around distributed compute, data orchestration, distributed storage, streaming infrastructure Strong knowledge of SQL and NoSQL databases, such as MySQL, Postgres, and MongoDB. Programming skills in Python Passion for building developer tools and scalable infrastructure Available to collaborate onsite 2 days a week Our Vibe: Relaxed work environment 100% paid top of the line health care benefits Full ownership, no micro management Strong equity package 401K Unlimited vacation An actual work/life balance, we aren't trying to run you into the ground. We have families and enjoy life too!

San Francisco, CA (Onsite) About the Company A fast-moving AI research group is building the core video data infrastructure used by leading AI labs and major tech companies. The team is small at around fifteen people, nearly all engineers, and recently pivoted to focus exclusively on high-quality video data at massive scale. The shift has driven significant revenue growth, and they are now planning to expand the team steadily over the next few months. The culture is straightforward: engineering led, product focused, low ego, and built around people who enjoy ownership. They work in person five days a week in their San Francisco office, moving quickly, solving hard problems, and avoiding micromanagement. The Role This position focuses on designing and scaling distributed systems that support huge ML and ETL workloads across petabytes of video. You will own core infrastructure: compute scheduling, orchestration, throughput, reliability, cost efficiency, and the internal tooling that keeps the entire engineering group moving at pace. The company is beginning to scale its infrastructure footprint aggressively, and this role will become central to that growth. It is a hands-on IC position suited to someone who has operated critical systems before and wants to shape the foundation of a rapidly expanding platform. What You'll Work On • Architect and scale distributed systems for large-scale ML and ETL workloads • Build compute orchestration and scheduling across thousands of GPUs • Improve uptime, resilience, and execution speed of high-volume data pipelines • Design pipelines capable of handling petabyte-level video datasets • Lead the development of CI/CD and internal tooling for fast iteration • Partner closely with research engineers delivering new video models and algorithms • Operate in a high-trust environment with strong autonomy and clear ownership Requirements • 3+ years building foundational distributed systems or data infrastructure • Experience running critical systems at significant scale • Proficient across cloud architectures • Strong coding experience with Go (preferred) and Python • Background building or maintaining large-scale pipelines • Experience with ML-focused CI/CD and automation • Video domain experience is not required • Operates as a strong IC who leads through action • Fully onsite in San Francisco, Monday to Friday Culture Fit • Enjoys ambiguity, problem discovery, and self-direction • Communicates clearly and concisely • Shows strong intellectual curiosity • Low ego, collaborative mindset • Motivated by building core systems in a small, high-caliber team Red flags include weak communication, low curiosity, or unclear motivation for the domain. Interview Process Intro call focused on culture, curiosity, and communication Technical discussion on background and complexity of past work Problem-solving session with a research engineer Onsite research problem and collaboration exercise

Staff / Lead ML Infrastructure Engineer San Francisco, CA - Onsite Salary - Over market average + equity We are building one of the world's leading generative video and multimodal AI platforms, and we're looking for a senior infrastructure engineer to drive the backbone that makes it possible. This role is ideal for an engineer from a top-tier tech company who has built cloud-scale systems, high-performance compute platforms, and battle-tested CI/CD pipelines that support complex ML workloads. What You'll Own Core ML Platform Architecture: Design and evolve the infrastructure that supports large-scale generative video and multimodal model training, evaluation, and deployment. High-Throughput Compute Systems: Build and optimize GPU/TPU clusters, distributed training systems, and orchestration layers tailored for video-heavy pipelines. Production Reliability for Generative Models: Create the tooling and services needed to safely push frequent model updates while handling massive compute loads and long-running jobs. End-to-End CI/CD for ML: Lead the development of automated pipelines for model training, validation, artifact management, and production rollout. Multimodal Data Infrastructure: Build systems to ingest, version, transform, and serve large-scale video, audio, and text datasets with high reliability. Internal Developer Experience: Partner with research, product, and applied ML teams to build intuitive internal tooling for experiment tracking, model lineage, and resource scheduling. Technical Leadership: Mentor engineers, set platform standards, and influence long-term architectural direction. What You've Done Experience architecting and operating large-scale infrastructure at a cloud provider, hyperscaler, or leading AI company. Built or owned mission-critical CI/CD systems, high-capacity compute platforms, or data infrastructure supporting ML teams. Deep experience with distributed compute across GPUs/accelerators, Kubernetes, and cloud infrastructure (AWS/GCP/Azure). Strong engineering fundamentals in Python, Go, or equivalent languages. Previous exposure to ML training pipelines-especially systems that handle heavy video, multimodal, or high-dimensional data. Demonstrated ability to lead complex cross-org initiatives and drive technical strategy. Nice to Have Experience with video processing systems, large-scale media pipelines, or streaming architectures. Familiarity with modern multimodal or video-generation frameworks (PyTorch, JAX, diffusers, custom accelerators). Experience with Ray, Triton, CUDA optimization, or specialized scheduling for ML workloads. Background working in high-growth AI startups or research-focused environments. Security and compliance considerations for models that generate or process user content. Why Join Shape the underlying platform powering one of the most advanced generative video systems in the world. Influence the future of multimodal AI by building infrastructure that directly accelerates research and product breakthroughs. Work closely with experienced founding engineers, researchers, and platform builders from leading tech companies. Highly competitive compensation, meaningful equity, and strong in-person engineering culture in San Francisco.