Model Evaluation Operator - AI Robotics (Swing Shift)

Why RoboForce RoboForce is an AI robotics company developing Physical AI–powered Robo-Labor for dull, dirty, and dangerous work. The company's robots are engineered for demanding industrial environments, with a focus on real-world deployment and scalability. We are looking for a Senior / Staff AI Research Engineer, Data Infrastructure to build the data and learning engine behind RoboForce's Physical AI stack. In this role, you will own the full pipeline — from raw teleoperation and UMI device data collection through curation, annotation, and storage, to post-training infrastructure that scores demonstrations, identifies failure patterns, and closes the loop back into model retraining. Responsibilities Design and maintain end-to-end data collection pipelines ingesting multimodal demonstration data from teleoperation devices and UMI hardware, including synchronization, versioning, and distributed storage at scale. Build annotation tooling and data curation workflows — quality filtering, deduplication, episode scoring, and domain reweighting — to produce high-quality training datasets for robot policy learning. Develop post-SFT reinforcement learning infrastructure: implement reward scoring on demonstrations, mine and categorize failure patterns, and feed curated failure data back into the retraining loop. Build evaluation and test infrastructure to log policy rollouts on-robot, capture structured results, and surface actionable diagnostics for the research team. Collaborate with ML researchers to define data schemas, episode formats, and pipeline interfaces that support rapid iteration on VLA and manipulation policy training. Architect scalable storage and retrieval systems for heterogeneous robot data (vision, proprioception, action, language) across both cloud and on-prem environments. Requirements Bachelor's or Master's degree in Computer Science, Robotics, or related field with 5+ years of experience. Strong proficiency in Python and experience build

About us Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation. Job Summary We are seeking a Sourcing Manager – AI Infrastructure to lead strategic sourcing activities across key infrastructure technologies supporting Graphcore’s AI compute platforms. Reporting into the Global Sourcing Management team, this role will partner closely with Engineering, Product, Operations, Manufacturing, and Supply Chain teams to develop sourcing strategies, manage supplier relationships, negotiate commercial agreements, and ensure resilient supply for critical infrastructure components. The successful candidate will combine strong commercial acumen with a solid understanding of AI infrastructure technologies, enabling effective engagement with suppliers and technical stakeholders while balancing cost, quality, delivery, scalability, and risk objectives. This role draws upon leading practices from AI infrastructure sourcing environments while aligning with Graphcore’s strategic sourcing model. The Team The Global Sourcing Management (GSM) team defines and executes supplier strategies across Graphcore’s hardware and infrastructure ecosystem. The team works closely with Engineering, Product Management, Operati

Why RoboForce RoboForce is an AI robotics company developing Physical AI–powered Robo-Labor for dull, dirty, and dangerous work. The company's robots are engineered for demanding industrial environments, with a focus on real-world deployment and scalability. We are looking for a Lead AI Research Engineer, Embodied Systems to lead and own the engineering of the systems that turn embodied AI into real-world robot behavior. You will be the technical owner and lead for the full embodied systems stack — the onboard AI system, the data collection system, the teleoperation systems, and the on-robot reinforcement learning system — driving the direction hands-on and closing the loop between data, models, and action in the physical world. Responsibilities Lead and own, from the engineering side, the embodied systems that power RoboForce's data flywheel — the onboard AI (inference) system, the data collection system, the teleoperation systems and the on-robot reinforcement learning system. Set the technical direction and architecture for how learned models run, are evaluated, and improve on real robots. Deliver these systems end-to-end on physical robots — from bring-up through reliable, real-time operation in demanding industrial environments. Own on-robot deployment and closed-loop evaluation of policies, turning real-world performance into measurable improvements. Partner with and influence the robotics software team and the ML research team to align interfaces and priorities across the stack. Grow the direction — mentor engineers and raise the technical bar for embodied systems work. Requirements Bachelor's or Master's degree in Computer Science, Robotics, Electrical Engineering, or related field with significant relevant experience, or a PhD degree. Track record of leading complex robotic or embodied systems end-to-end and setting technical direction for other engineers. Strong proficiency in both C++ and Python, with solid systems programming and real

Why RoboForce RoboForce is an AI robotics company developing Physical AI–powered Robo-Labor for dull, dirty, and dangerous work. The company’s robots are engineered for demanding industrial environments, with a focus on real-world deployment and scalability. We are hiring a Lead AI Native Engineer to build RoboForce’s vertical agents and shared agent foundation. Reporting to the co-founder, you will turn frontier models into systems for strategy and engineering. This is a hands-on technical leadership role: you will write code, set architecture, and enable agent development—not lead People programs or organizational transformation. Responsibilities Build vertical agents. Own end-to-end agents for high-value workflows across research, software, hardware, data, and operations—from problem definition through production use. Establish the agent foundation. Build reusable primitives for models, tools, orchestration, context, memory, retrieval, permissions, human approval, and long-running execution. Create the context layer. Connect agents to trusted data through APIs, pipelines, MCP servers, and integrations with clear provenance and access control. Own evaluation and reliability. Build benchmarks, regression tests, tracing, monitoring, and failure-analysis loops across quality, latency, cost, security, and resilience. Advance frontier agent usage. Evaluate new models, coding agents, SDKs, and patterns, then turn useful capabilities into maintainable systems rather than demos. Support strategic initiatives. Help company leadership apply agents and analytical systems to market and customer intelligence, partnerships, fundraising, diligence, scenario analysis, and executive decisions. Provide technical leadership. Set architecture and engineering standards, review designs and code, and create reusable patterns for the technical team. Requirements 5+ years in software engineering, applied AI, ML systems, or a related field, with strong zero-to-one technical judgment. Exper

About Graphcore Graphcore is a leading innovator in artificial intelligence computing. We develop hardware, software, and data center infrastructure that provide the specialized processing and systems capabilities needed to advance AI while improving the efficiency required for broad adoption. As part of SoftBank Group, Graphcore works alongside companies developing advanced technologies. Our teams bring together AI researchers, silicon designers, hardware and software engineers, and systems architects to solve complex technical problems across the computing stack. The Opportunity As Principal Storage Architect, you will define the high-performance storage architecture for Graphcore's AI computing and data center infrastructures. You will lead the design of local and distributed storage tiers that provide the throughput, availability, and predictable tail latency required for large-scale training and inference. Working within Advanced Architecture, you will address storage requirements for saving model states, offloading key-value caches, large datasets, and high-speed data-loading pipelines. You will combine hands-on performance engineering with Principal-level technical leadership across hardware, software, networking, systems engineering, automation, supply chain, and external technology partners. What You Will Do Define the end-to-end architecture and technology roadmap for local, disaggregated, and distributed storage across Graphcore AI server and data center platforms. Design storage topologies that optimize PCIe lane allocation, network-domain placement, and data paths among CPUs, AI accelerators, memory, and storage systems. Lead the architecture of storage control-plane and data-plane solutions, evaluating commercial and open technologies against performance, resilience, manageability, and lifecycle requirements. Profile and tune the Linux storage stack, block layer, I/O schedulers, direct I/O paths, file systems, and drivers to imp

About Graphcore Graphcore is a leading innovator in artificial intelligence computing. We develop hardware, software, and data center infrastructure that provide the specialized processing and systems capabilities needed to advance AI while improving the efficiency required for broad adoption. As part of SoftBank Group, Graphcore works alongside companies developing advanced technologies. Our teams bring together AI researchers, silicon designers, hardware and software engineers, and systems architects to solve complex technical problems across the computing stack. The Opportunity As Principal Datacenter Technologist, you will turn new platform architectures into repeatable operating models for Graphcore's AI data centers. You will lead the technical definition of how Graphcore introduces, deploys, services, and sustains new compute, networking, storage, memory, power, and cooling technologies at scale. Working within Advanced Architecture, you will connect platform design with data center engineering and site reliability operations. You will define new-product-introduction workflows, readiness criteria, diagnostics, and cross-functional handoffs so that new systems can move from architecture through deployment with clear ownership, supportability, and operational feedback. What You Will Do Own the technical operating model and new-product-introduction framework for new hardware and infrastructure technologies entering Graphcore data centers. Define end-to-end workflows for installation, configuration, validation, deployment, service, repair, upgrade, and sustained operation across the product lifecycle. Translate architecture requirements into data center readiness criteria covering software, firmware, compute, networking, storage, memory, rack integration, power, cooling, space, and site operations. Create clear runbooks, interface definitions, ownership models, acceptance criteria, and escalation paths that align architecture, engineering, data center, and site r