Full-Time
Senior Software Engineer
Posted on 5/29/2025
Clockwork Systems
1-10 employees
Advanced clock synchronization for distributed systems
No salary listed
Palo Alto, CA, USA
In Person
 Software Engineering (1) |
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- At least 5 years of industry experience.
- A degree in computer science, electrical engineering or related field.
- Fluency in one or more languages: C, C++, Golang, Java, Python.
- Excellent communication skills.
- Excellent debugging and problem solving skills.
- Experience designing, building and scaling large distributed systems in production.
- Experience with service-oriented architectures and cloud technologies (AWS, GCP, Azure).
- Experience with operating systems concepts including threads, scheduling, process synchronization, and kernel programming.
- Experience with database builds.
- Knowledge of networking protocols.
- Design the next generation of network acceleration software.
- Lead or contribute directly to the design and build of high performance, reliable and scalable systems.
- Design, build and scale large distributed systems in production.
- Work with service-oriented architectures and cloud technologies (AWS, GCP, Azure).
- Work with operating systems concepts including threads, scheduling, process synchronization, and kernel programming.
- Work on database builds.
- Work on networking protocols; NIC architecture and operation is a plus.
- Full stack development.
- Networking protocols experience or NIC architecture and operation is a plus.
- Full stack development.
Clockwork Systems provides clock synchronization technology for mission-critical distributed systems, ensuring precise timing across operations. Its solutions run in both cloud and on-premises environments and are delivered through software licensing, subscriptions, and professional services. The company differentiates itself with deep timing expertise and end-to-end timing across networks, framed by tools like Latency Sensei for cloud latency monitoring. Its goal is to help customers achieve reliable, accurate synchronization to boost performance and reduce timing-related issues in time-sensitive applications.
Company Size
1-10
Company Stage
Early VC
Total Funding
$41.6M
Headquarters
Palo Alto, California
Founded
2018
Simplify's Take
What believers are saying
- Raised $20.6M Series A in 2022 led by NEA for FleetIQ launch.
- Serves hyperscalers, banks, pharma labs optimizing model training.
- Hired NetApp exec Suresh Vasudevan as CEO in 2025.
What critics are saying
- NVIDIA software stack bundles GPU management, blocks penetration in 12-24 months.
- Hyperscalers like Meta, Google build proprietary fabrics in 18-36 months.
- Customer concentration risks 30-50% revenue loss from one cloud exit.
What makes Clockwork Systems unique
- FleetIQ delivers microsecond visibility into GPU clusters for AI workloads.
- Software-driven fabric runs on NVIDIA, AMD, InfiniBand, RoCE, Ethernet.
- Stanford spinout founded 2018 extends clock sync to AI training.
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Benefits
Competitive Salary
Company News
Clockwork.io has launched TorchPass Workload Fault Tolerance, a software solution that eliminates costly GPU training failures through Live GPU Migration technology. The system allows AI training workloads to continue running through hardware failures, network disruptions and node crashes without requiring checkpoint restarts. The company claims TorchPass can save over $6 million annually in a typical 2,048-GPU deployment by reducing wasted training progress by 95%. In large clusters, it cuts lost time from approximately three hours per day to under ten minutes. Independent testing by SemiAnalysis found TorchPass delivered faster fault-tolerant performance than standard checkpoint-restart approaches and higher Model FLOPs Utilisation than leading open-source alternatives. The solution typically completes recovery in approximately three minutes whilst training continues uninterrupted. TorchPass is now available as part of Clockwork.io's FleetIQ platform.
Clockwork Raises $20.57 Million in Funding
Stanford spinout Clockwork has raised $20.6 million, led by NEA with participation from notable investors, to address AI's GPU inefficiency. The funding coincides with the launch of FleetIQ, a software solution aimed at enhancing GPU performance by improving communication between GPUs, clusters, and clouds. This innovation seeks to reduce crashes, shorten restarts, and increase utilization rates, making AI infrastructure more efficient and sustainable.