Distributed Systems Engineer
WFA Digital Insight
The demand for skilled distributed systems engineers grew significantly in 2025, with a 28% increase in job postings. Menlo Research is at the forefront of this trend, building a revolutionary open-source humanoid robot platform. This role stands out for its unique blend of distributed systems, robotics, and AI, offering a challenging and rewarding experience for the right candidate. With over 75% of companies adopting cloud-native architectures, expertise in Kubernetes, gRPC, and Kafka is highly valued. Before applying, candidates should be prepared to showcase their ability to design and operate production-grade distributed systems, as well as their passion for innovation and collaboration.
Job Description
About the Role
As a Distributed Systems Engineer at Menlo Research, you will be responsible for architecting and scaling the infrastructure that powers fleets of humanoid robots operating across the world. You will work across the full stack of robotics infrastructure, from low-latency streaming and cloud simulation to large-scale training and telemetry pipelines. This role is critical to the success of Menlo's mission to make humanoid labor economically viable.The Distributed Systems Engineer will work directly with the founders and technical leadership to design the systems that let hundreds of robots learn, share, and act as one. This is a unique opportunity to join a tight-knit team defining the next generation of humanoid robots, with genuine ownership of system architecture and the freedom to innovate.
Menlo Research is committed to creating a collaborative and open environment, where employees can thrive and grow. With a strong focus on innovation and experimentation, the company encourages its engineers to push the boundaries of what is possible with distributed systems and robotics.
What You Will Do
- Architect and scale distributed systems that handle petabytes of sensory, telemetry, and control data across cloud and edge environments
- Design data ingestion and streaming pipelines connecting fleets of robots to the cloud in real time (video, LiDAR, joint states, audio)
- Build large-scale training and inference platforms for multimodal foundation models powering robot autonomy and teleoperation
- Collaborate with ML and Robotics engineers to support hardware-in-the-loop simulation, policy rollout, and continuous learning
- Develop internal observability systems for fleet monitoring, reliability, and performance tuning
- Lead infrastructure decisions, from distributed storage and consensus protocols to GPU orchestration and network reliability
- Work with the team to identify and prioritize key performance indicators (KPIs) for the distributed systems
- Participate in the design and implementation of automated testing and deployment scripts
- Contribute to the development of best practices and standards for distributed systems engineering
What We Are Looking For
- 7+ years of professional software engineering experience, with deep expertise in distributed systems, networking, or data infrastructure
- Proven ability to build and operate production-grade distributed systems handling massive scale and mission-critical workloads
- Proficiency in Go, Rust, C++, or Python, with strong fundamentals in concurrency, networking, and systems performance
- Experience with cloud-native architectures (Kubernetes, gRPC, Kafka, S3, Ray, or similar frameworks)
- Strong understanding of data consistency, replication, and fault tolerance across heterogeneous environments
- Experience with GPU-based workloads, model training, or edge compute orchestration
- Excellent analytical skills and a bias toward building fast, measurable, and reliable systems
- Strong communication and collaboration skills, with experience working with cross-functional teams
Nice to Have
- Experience building distributed training or large-scale simulation systems
- Familiarity with real-time robotics workloads, including streaming from physical sensors and actuators
- Prior work with telemetry, observability, or fleet-scale systems in production
- Contributions to open-source infrastructure, AI frameworks, or robotics middleware (ROS, gRPC, Mediasoup, etc.)
Benefits and Perks
- Competitive salary and benefits package
- Opportunity to work on a revolutionary open-source humanoid robot platform
- Collaborative and open work environment with a team of experienced engineers
- Flexible working hours and remote work options
- Professional development opportunities, including conference attendance and training
- Access to cutting-edge technology and tools
- Recognition and reward for outstanding performance and contributions
- Comprehensive health insurance and retirement plan
- Generous paid time off and holiday policy
How to Stand Out
- When applying for this role, make sure to highlight your experience with distributed systems, cloud-native architectures, and robotics.
- Showcase your ability to design and operate production-grade distributed systems, and be prepared to provide specific examples.
- Familiarize yourself with Menlo Research's technology stack and be prepared to discuss your experience with similar tools and frameworks.
- Demonstrate your passion for innovation and collaboration, and highlight your ability to work effectively in a cross-functional team.
- Be prepared to discuss your understanding of data consistency, replication, and fault tolerance, and how you would approach these challenges in a distributed system.
- Consider creating a personal project or contributing to an open-source project to demonstrate your skills and experience with distributed systems and robotics.
- Practice your coding skills and be prepared to complete a technical challenge or coding exercise as part of the interview process.
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