Total 6 job vacancies by Menlo Research Pte. Ltd.

About Asimov

Asimov is Menlo's flagship open-source humanoid robotics initiative. We are building every layer of the stack, from precision mechanical structures and actuators to control hardware, firmware, and AI. Software is the connective tissue that makes all of it work.

The Role

As a Software Engineer on the Asimov team, you will build and maintain the software systems that power our humanoid robot, from low-level hardware integration to the interfaces and tooling that researchers and engineers depend on daily. You will work across the stack, bridging robot hardware, control systems, and the developer-facing surfaces that make Asimov programmable and observable.

What You'll Do

• Research, design, and develop software and specialised utility programs across the Asimov robotics stack
• Analyse requirements from hardware, firmware, and controls teams and translate them into reliable software solutions, applying principles of computer science, engineering, and systems design
• Update and enhance existing software capabilities, and develop and direct software testing and validation procedures to ensure correctness and performance
• Work directly with hardware and firmware engineers to integrate hardware and software systems, and develop specifications and performance requirements
• Build and maintain interfaces between robot hardware, control loops, and higher-level software systems
• Develop internal tooling, dashboards, and visualisation layers for robot state, sensor data, and system health
• Contribute to Asimov's open-source releases including software libraries, APIs, and developer documentation

What You'll Bring

• 3 years of software engineering experience, with meaningful ownership of shipped systems
• Proficiency in Python and C++ in a production or near-production context
• Experience building across the stack, comfortable working close to hardware interfaces as well as on application or tooling layers
• Solid understanding of systems programming concepts: processes, threading, IPC, memory management
• Familiarity with ROS or ROS2, or strong motivation to get up to speed quickly
• Experience writing and maintaining test suites and validation pipelines
• Strong communication skills and comfort working in cross-disciplinary teams alongside mechanical, electrical, and firmware engineers

Bonus points for

• Prior experience in robotics, autonomous systems, or embedded software environments
• Familiarity with real-time systems or low-latency data pipelines
• Experience with CAN bus, serial protocols, or hardware bring-up support
• Contributions to open-source robotics or hardware projects
• Exposure to simulation environments such as Isaac Sim, MuJoCo, or Gazebo

Why Join Menlo?

You will be part of a small, focused team building one of the most technically ambitious open-source robotics platforms in the world. You will have real ownership across the stack, work directly with the hardware your software runs on, and ship code that moves a humanoid robot.

About Asimov
Asimov is Menlo's flagship open source humanoid robotics initiative. We are building every layer of the stack, from precision mechanical structures, injection molded plastics, and die cast components to actuators, sensors, control hardware, firmware, and AI.

The Role
As a Mechanical Engineer, you will own the conception, CAD modeling, and industrialization of humanoid components across the full body. You will translate early concepts into robust, production ready designs, guide prototype builds, and partner with suppliers to ramp tooling and volume manufacturing. This is a high ownership role where your design decisions will directly determine how Asimov moves, holds up, and scales.

What You'll Do

• Develop detailed 3D part and assembly models across plastics, sheet metal, die cast, and composite materials in CATIA or equivalent CAD tools.
• Drive rapid prototyping by overseeing 3D printing, CNC machining, and initial fit check assemblies, iterating quickly from concept to physical hardware.
• Perform tolerance studies, FEA, and kinematic simulations to validate stiffness, strength, and lifetime requirements across joints and structural members.
• Create accurate production drawings with GD&T annotations and critical inspection call outs for manufacturing and QA handoff.
• Conduct DFM reviews with contract manufacturers and tooling partners, refining designs for cost, cycle time, and quality at low to medium volume.
• Work alongside electrical, firmware, and validation teams to integrate mechanical systems with sensors, wiring harnesses, and PCBA enclosures.
• Define mechanical test protocols, analyze failure modes, and iterate designs based on test data and reliability metrics.
• Contribute to Menlo's open source design efforts, including CAD releases, manufacturing documentation, and build guides for the broader robotics community.

What You'll Bring

• 3 or more years of hands on mechanical design experience for high complexity electromechanical products.
• Expert proficiency in CATIA V5/V6, with strong ability to produce both detailed parts and multibody assemblies.
• Proven track record with plastic injection molding, sheet metal fabrication, and die casting processes.
• Solid understanding of GD&T and the ability to produce 2D engineering drawings for manufacturing and QA.
• Experience running FEA simulations across stress, thermal, and modal analyses, and interpreting results to inform design decisions.
• Ability to work within aggressive cost and weight constraints, making principled tradeoffs without sacrificing reliability.
• Strong communication skills to drive alignment across suppliers, cross disciplinary engineers, and leadership.

Bonus Points

• Experience with bipedal or humanoid robot hardware, legged locomotion platforms, or high DOF manipulators.
• Familiarity with parallel mechanisms and non standard joint configurations such as RSU ankle designs or parallel actuation.
• Knowledge of plastics engineering including material selection, shrinkage factors, and mechanical property optimization.
• Scripting or automation experience in Python to streamline CAD workflows and data analysis.
• Familiarity with MATLAB for system level modeling and tolerance stack ups.
• Hands on background with rapid iteration prototyping tools including 3D printers, laser cutters, and CNC mills.
• Prior involvement in robotics or wearable systems where mechanical tolerances and ergonomics are critical.
• Familiarity with CAN bus, motor controllers, and how mechanical design choices affect firmware and control integration.
• Familiarity with sim to real workflows and how hardware decisions affect locomotion policy training and transfer.

Why Join Menlo?
You’ll be part of a tight-knit team defining the next generation of humanoid robots. With genuine ownership of system architecture and the freedom to innovate, you’ll see your designs come to life in real-world deployments. If you thrive in fast-paced, open-collaborative environments, let’s build the future of robotics together.

About Asimov
Asimov is Menlo's open source humanoid robotics platform, building every layer from structural frames and electromechanical assemblies to power electronics, embedded control hardware, firmware, and AI. We also build Jan, our open source AI assistant used by millions of developers worldwide. Our goal is to democratize advanced robotics and AI by sharing designs, models, and infrastructure with the global community.

The Role
We are looking for a Platform Lead to own and evolve the full infrastructure stack that powers both our humanoid robotics fleet and our developer facing AI platform. This is a senior technical leadership role sitting at the intersection of distributed systems, high performance APIs, and production AI infrastructure. You will work directly with the founders and technical leadership to design systems that let hundreds of robots learn and act as one, while also enabling developers and partners to build on top of Menlo's intelligent platform. If you thrive on hard technical problems at massive scale and want genuine ownership over platform architecture, this role is for you.

What You'll Do

• Architect and scale distributed systems that handle petabytes of sensory, telemetry, and control data across cloud and edge environments, connecting fleets of robots in real time.
• Design and build the Menlo API Platform, delivering high reliability, world class developer experience, and production grade multimodal AI capabilities via intuitive APIs and SDKs.
• Build large scale training and inference platforms for multimodal foundation models powering robot autonomy, teleoperation, and developer integrations.
• Design data ingestion and streaming pipelines connecting robot fleets to the cloud in real time, covering video, LiDAR, joint states, and audio.
• Manage and evolve a modern cloud native infrastructure stack using Kubernetes, Docker, and infrastructure as code tooling.
• Ensure platform reliability through telemetry, monitoring, alerting, autoscaling, failover, and disaster recovery mechanisms.
• Lead infrastructure decisions spanning distributed storage, consensus protocols, GPU orchestration, network reliability, and API security.
• Collaborate across ML, robotics, and product teams to support hardware in the loop simulation, policy rollout, continuous learning, and CI/CD workflows.
• Implement secure APIs with fine grained access control, usage metering, rate limiting, and billing integration as we scale to serve millions of users.

What You'll Bring

• 7 or more years of professional software engineering experience with deep expertise in distributed systems, backend infrastructure, or data platforms.
• Proven ability to build and operate production grade systems handling massive scale and mission critical workloads.
• Proficiency in Go, Rust, C++, Python, or TypeScript, with strong fundamentals in concurrency, networking, and systems performance.
• Deep experience with cloud native architectures including Kubernetes, Docker, Helm, gRPC, Kafka, Ray, and service mesh technologies such as Istio or Linkerd.
• Strong understanding of API architecture and design patterns including REST, gRPC, WebSockets, OAuth2, and OpenAPI.
• Experience with databases spanning PostgreSQL, Redis, and modern vector databases such as Pinecone, Weaviate, or FAISS.
• Strong understanding of data consistency, replication, and fault tolerance across heterogeneous environments.
• Familiarity with observability tooling such as Prometheus, Grafana, Datadog, or OpenTelemetry applied to large scale production systems.

Bonus Points

• Experience building distributed training, large scale simulation, or fleet scale telemetry systems.
• Familiarity with real time robotics workloads including streaming from physical sensors and actuators.
• Experience with MLOps tools and AI workflows including model versioning, inference pipelines, and model registries.
• Knowledge of billing systems, quota enforcement, chargeback models, and multi tenant security and isolation.
• Prior experience on developer platforms or API products with a strong focus on developer UX and documentation.
• Contributions to open source infrastructure, AI frameworks, or robotics middleware such as ROS, gRPC, or Mediasoup.

Why Join Menlo? 
You will be part of a tight knit team defining the next generation of humanoid robots and open AI infrastructure. With genuine ownership over platform architecture and the freedom to make bold technical decisions, you will see your systems power real robots in real world deployments. If you thrive in fast paced, open collaborative environments and want to build infrastructure that actually matters, let's build the future of robotics together.

About Us

We are working on embodied intelligence. Our mission is to scale general-purpose autonomy for real world problems (the 3Ds), through large-scale learning, multi-modal data, and robust control.We are looking for passionate engineers and scientists who thrive at the intersection of machine learning, robotics, and systems engineering, and want to see their research come alive in real robots.

Role Overview

You will lead development of the algorithms and architectures that enable our robots to achieve stable, responsive, and life-like movement in challenging conditions. This role demands deep knowledge of physical systems, control mechanisms, and foundational AI model research. You will design learning systems that power whole-body locomotion and real-world manipulation.

Responsibilities

• Design and implement models, e.g. RL policies for whole-body locomotion, enabling robots to walk, dance, balance, and recover from disturbances
• Develop novel observation spaces, action representations, and reward functions grounded in fundamental robotics principles
• Create and refine control strategies for real-time execution
• Optimize and evaluate locomotion policies in both simulated environments and on Asimov, our open source, humanoid reference design
• Pioneer techniques to enhance sim-to-real transfer, bridging the gap between virtual testing and physical deployment
• Collaborate closely with simulation, hardware, and autonomy teams to ensure seamless integration of locomotion systems
• Deploy production-ready locomotion policies to our fleet of operational humanoid robots
• Contribute to the advancement of robotics research through publications and open-source contributions

Preferred Qualifications

• BS/MS/PhD in Robotics, AI/Computer Science, or related field
• Solid understanding of robotics fundamentals, including geometry, linear algebra, kinematics, dynamics, probability, and statistics 
• Experience working with robotic systems, ideally on legged robotic systems with high degrees of freedom
• Experience implementing control strategies including impedance control, adaptive control, force control, MPC on hardware preferred 
• Experience with sim2real techniques OR deep understanding of physics fundamentals
• Familiarity with Machine learning and Reinforcement Learning fundamentals OR strong background in optimization-based planning and control 

Bonus Skills

• Work on humanoid locomotion, manipulation, or whole-body coordination
• Prior open-source or research contributions in robotics, control, or deep learning

About Us
We are working on embodied intelligence. Our mission is to scale general-purpose autonomy for real world problems (the 3Ds), through large-scale learning, multi-modal data, and robust control. We are looking for passionate engineers and scientists who thrive at the intersection of machine learning, robotics, and systems engineering, and want to see their research come alive in real robots.

Role Overview
You will lead development of the algorithms and architectures that enable our robots to interact with and reason about the physical world. This role bridges world model research, embodied AI, and real-time robotics. You will engineer models and learning systems that power robotic agents through real world jobs.

Responsibilities

• Train and adapt large-scale VLA & VLMs that predict multi-modal futures (video, proprioception, audio, actions)
• Develop systems for cross-modal grounding, enabling robots to interpret sensor data in context and build coherent world models
• Enable temporal reasoning and goal-directed behavior through hierarchical task decomposition and meta-reasoning
• Support human-robot interaction by recognizing intentions, interpreting social cues, and enabling collaborative workflows
• Deploy models into real-time humanoid and mobile robots
• Evaluate and scale pipelines to measure generalization and safety
• Collaborate with locomotion, simulation and hardware teams to bridge sim-to-real transfer
• Publish and open source datasets, models, papers in parallel

Preferred Qualifications

• BS/MS/PhD in Robotics, AI/Computer Science, or related field
• Proficiency in Python and C++, and deep learning frameworks (PyTorch / JAX)
• Deep experience in GenAI, RL/IL, control, or multimodal learning
• Understanding of scaling laws, evaluation metrics, and scaling training for large models
• Familiarity with real-robot systems, sensing, and embedded control integration
• Familiarity with industry SOTA and latest research, e.g. Gr00t, Pi0, etc

Bonus Skills

• Experience with transformer-based control policies or diffusion policy learning.
• Work on humanoid locomotion, manipulation, or whole-body coordination.
• Prior open-source or research contributions in robotics, control, or deep learning.

About Asimov
Asimov is our open‐source humanoid robotics platform, building every layer—from structural frames and electromechanical assemblies to power electronics, cabling, and embedded control hardware. We aim to democratize advanced robotics by sharing designs, firmware, and ML models with the global community. 

The Role
We’re looking for a Distributed Systems Engineer to architect and scale 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. You’ll work directly with the founders and technical leadership to design the systems that let hundreds of robots learn, share, and act as one.

What You’ll 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.

What You’ll Bring

• 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 is a strong plus.
• Excellent analytical skills and a bias toward building fast, measurable, and reliable systems.

Bonus Points

• 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.).

Why Join Menlo?
You’ll be part of a tight-knit team defining the next generation of humanoid robots. With genuine ownership of system architecture and the freedom to innovate, you’ll see your designs come to life in real-world deployments. If you thrive in fast-paced, open-collaborative environments, let’s build the future of robotics together.