Modular

Role Description In the Cloud Inference team, we are focused on building end to end distributed LLM inference deployments that are fully vertically integrated with the MAX stack. Our goal is to make inference both the fastest and most scalable while also building an easiest platform for deploying and scaling models for enterprises and developers alike. We're seeking engineers who are passionate about pushing the boundaries of distributed inference systems and enjoy working at the intersection of large-scale systems and machine learning. We are looking for candidates based on their breadth and depth of experience in backend engineering, AI inference, and distributed systems development. If this sounds exciting, we invite you to join our world-leading AI infrastructure team and help drive our industry forward! What you will do: - Build & ship a LLM focused inference platform using best in class inference techniques (disaggregated inference, multi-node deployment of large models, high performance networking, distributed kv-cache management, high throughput batch processing, etc). - Push the envelope for operational excellence with request-to-kernel observability, multi-cloud deployments, clever autoscaling, cold-start optimizations, and more. - Collaborate with our kernels and genAI teams to achieve SOTA application performance by integrating SOTA kernel & serving optimizations with SOTA cluster optimizations. - Build helm charts, kubernetes operators, and more to make a create simple, effective, maintainable deployments. Qualifications - 5+ years of experience working in backend engineering. - Experience with kubernetes and operating your own services. - Ability to create durable, reusable software tools and libraries that are leveraged across teams and functions. - Experience in machine learning technologies and use cases. - Creativity and curiosity for solving complex problems, a team-oriented attitude that enables you to work well with others, and alignment with our culture. - Strongly identifies with our core company cultural values. Helpful but not required: - Experience with high performance computing / networking. - Experience working on high scale ML inference infrastructure (traditional AI or genAI). - Familiarity with golang. Benefits - Amazing Team: We are a progressive and agile team with some of the industry’s best engineering and product leaders. - World-class Benefits: Premier insurance plans, up to 5% 401k matching, flexible paid time off, and more are available to you! - Competitive Compensation: We offer very strong compensation packages, including stock options. - Team Building Events: We organize regular team onsites and local meetups in Los Altos, CA as well as different cities. Traveling 2-4 times a year is expected for all roles. Salary Information The estimated base salary range for this role to be performed in the US, regardless of the state, is $166,500.00 - $273,000.00 USD. The estimated base salary range for this role to be performed in Canada, regardless of the province, is $158,000.00 - $258,000.00 CAD. The salary for the successful applicant will depend on a variety of permissible, non-discriminatory job-related factors, which include but are not limited to education, training, work experience, business needs, or market demands. Equal Opportunity Employer Modular is proud to emphasize an equal opportunity, safe environment for people to do their best work. Modular is an affirmative action employer. We are committed to providing equal employment opportunities regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status.

Role Description At Modular, we optimize inference from kernel to cloud on one unified stack. We are building a differentiated cloud platform that delivers state of the art inference performance from day one, then keeps getting better. As we learn the shape and patterns of each customer's workload, the platform adapts and improves performance automatically over time. The Performance Labs team builds the infrastructure that makes this possible at scale. We continuously apply the latest optimizations across kernels, the inference engine, and distributed systems so that customer workloads stay on the Pareto frontier of cost and performance. We get there through deep workload insights, a scalable platform, and close collaboration with engineering and product teams. In this role you will lead a high impact team that partners closely with GTM, Product, and Engineering to redefine what an inference platform can be. You will turn real customer workloads into a continuous optimization loop, shape the product direction of Modular Cloud, and build the systems that let performance scale with demand. LOCATION: Candidates based in the US or Canada are welcome to apply. You can work in our office in Los Altos, CA or remotely from home. Onboarding for new hires is conducted in-person in our Los Altos, CA office. What you will do: - Lead the team that builds the optimization platform driving LLM inference on Modular Cloud to state of the art performance across the latest GPU and ASIC architectures. - Own the technical direction of Modular Cloud, delivering LLM performance on the Pareto frontier for agentic use cases and keeping it there as the landscape evolves. - Partner closely with the GTM team to deliver highly customized LLM inference tuned to specific customer workloads, and collaborate across engineering to drive optimizations spanning the full stack, from GPU kernels to cloud infrastructure. - Translate insights from customer engagements into a clear technical roadmap that engineering teams can execute against. - Grow and develop a high impact team, set priorities, and create the conditions for engineers to do their best work on hard performance problems. - Champion the team externally through blog posts on innovative approaches to LLM inference optimization that shape industry wide best practices. Qualifications - 5+ years in distributed systems or performance engineering, including experience leading or managing engineering teams. - A track record of shipping durable, reusable software tools and libraries adopted across teams and functions, and of guiding a team to do the same. - Sound judgment in evaluating technical tradeoffs and setting priorities, paired with strong communication and technical leadership skills. - The ability to translate ambiguous customer and product needs into focused engineering direction. - Creativity and curiosity in solving complex problems, a collaborative and team oriented mindset, and alignment with our culture. Requirements - Hands on background in GPU kernel programming, inference engine internals, or distributed inference architectures. - Experience with Kubernetes and cloud native ecosystems. - Familiarity with modern LLM architectures and the latest inference optimization techniques. Benefits - Amazing Team: We are a progressive and agile team with some of the industry’s best engineering and product leaders. - World-class Benefits: In order to attract the best, we need to offer the best. Premier insurance plans, up to 5% 401k matching, flexible paid time off, and more are available to you! - Competitive Compensation: We offer very strong compensation packages, including stock options. - Team Building Events: We organize regular team onsites and local meetups in Los Altos, CA as well as different cities. Traveling 2-4 times a year is expected for all roles. Company Description Working at Modular will enable you to grow quickly as you work alongside incredibly motivated and talented people who have high standards, possess a growth mindset, and a purpose to truly change the world. The estimated base salary range for this role to be performed in the US, regardless of the state, is $234,000.00 - $286,000.00 USD. The estimated base salary range for this role to be performed in Canada, regardless of the province, is $229,000.00 - $280,000.00 CAD. The salary for the successful applicant will depend on a variety of permissible, non-discriminatory job-related factors, which include but are not limited to education, training, work experience, business needs, or market demands. This range may be modified in the future. The total compensation for a candidate will also include annual target bonus, equity, and benefits, with equity making up a significant portion of your total compensation. For candidates who fall outside of the listed requirements, we nevertheless encourage you to apply as we may have openings that are lower/higher level than the ones advertised.

Role Description At Modular, we optimize inference from kernel to cloud on one unified stack. We are building a differentiated cloud platform that delivers state of the art inference performance from day one, then keeps getting better. As we learn the shape and patterns of each customer's workload, the platform adapts and improves performance automatically over time. The Performance Labs team builds the infrastructure that makes this possible at scale. We continuously apply the latest optimizations across kernels, the inference engine, and distributed systems so that customer workloads stay on the Pareto frontier of cost and performance. In this role you will: - Dig into real customer inference workloads and profile them end to end. - Apply optimizations across kernels, engine, and distributed systems to push each workload toward the Pareto frontier. - Build the tooling and platform that turns one-off performance wins into a repeatable, automated optimization loop. - Work directly with engineering, product, and GTM to bring those gains to customers in production. Qualifications - 5+ years of experience in distributed systems or performance engineering. - A track record of building durable, reusable software tools and libraries that are adopted across teams and functions. - Sound judgment in evaluating technical tradeoffs and setting priorities. - Strong communication and technical leadership skills. - Creativity and curiosity in solving complex problems. - A collaborative and team-oriented mindset, aligned with our culture. Requirements - Experience with GPU kernel programming, inference engine internals, or distributed inference architectures (helpful, but not required). - Experience with Kubernetes and cloud native ecosystems (helpful, but not required). - Familiarity with modern LLM architectures and the latest inference optimization techniques (helpful, but not required). Benefits - Amazing Team: We are a progressive and agile team with some of the industry’s best engineering and product leaders. - World-class Benefits: Premier insurance plans, up to 5% 401k matching, flexible paid time off, and more are available to you! - Competitive Compensation: Very strong compensation packages, including stock options. - Team Building Events: Regular team onsites and local meetups in Los Altos, CA, and different cities. - Growth Opportunities: Work alongside incredibly motivated and talented people who have high standards and a growth mindset.

Role Description Within the Modular Platform Engineering group, we seek to understand and apply the capabilities that drive software delivery performance at Modular. We are heavily data driven and make use of the dora metrics to track progress as we run experiments to determine the impact of our team’s initiatives and investments. We are looking for candidates based on both their breadth and depth of experience from any number of specialties such as: - Software engineering - IAAS and PAAS - Test, build, compiler, kernel - Hardware - Machine learning We focus on compounding improvements of customer value delivery and exponential gains in velocity and quality. The goal is to bring together diverse, collaborative teams for intensive project work. We are a growing team who collaborate across disciplines on a day to day basis. A strong cross-collaborator is a must. Come and be part of our team and architect our software development life cycle at Modular. Join our world-leading AI infrastructure team and help drive our AI infrastructure stack forward. LOCATION: Candidates based in the US or Canada are welcome to apply. You can work out of one of our offices in Los Altos, CA, or remotely from home. What you will do: - Build monitoring, alerting and observability for Modular Software Development Life Cycle services. - Support internal engineers to help facilitate the future of ML software stacks. - Develop highly reliable and scalable services for developing, testing, and benchmarking across diverse OS and hardware targets. Qualifications - 4+ years of systems design experience such as distributed systems, high-performance concurrency, etc. - Experience building, deploying, and supporting cloud services (bonus points for multi-cloud). - Ability to create durable, reusable software frameworks that are leveraged across teams and functions. - Develops secure and high-quality production code, and reviews and debugs code written by others. - Experience with one or more cloud application programming languages (C, C++, Java, C#, Go etc.) and modern scripting languages (Bash, Python, etc). - Strong collaboration skills, ability to share information with internal and external engineering and product teams. - Experience, or deep interest, in machine learning technologies and use cases. - Creativity and curiosity for solving complex problems, a team-oriented attitude that enables you to work well with others, and alignment with our culture. - Experience using open source software components in production. - Devotion to quality and engineering excellence. - Strong written and verbal communication skills. - Strongly identifies with our core company cultural values. Requirements - Helpful but not required: LLVM, MLIR, or Python experience is a bonus. Benefits - Amazing Team: We are a progressive and agile team with some of the industry’s best engineering and product leaders. - Flexible Location: We want you to work where you are most productive and we are a remote-first company. We have offices in Palo Alto, CA and Seattle, WA for collaboration, and will open more next year. - World-class Benefits: In order to attract the best, we need to offer the best. Premier insurance plans, up to 5% 401k matching, very generous WFH setup stipends, flexible paid time off, and more are available to you! - Competitive Compensation: We offer very strong compensation packages, including stock options. We want people to be focused on their best work and believe in tailoring compensation plans to meet the needs of our workforce. - Team Building Events: We organize regular team onsites and local meetups in different cities. Working at Modular will enable you to grow quickly as you work alongside incredibly motivated and talented people who have high standards, possess a growth mindset, and a purpose to truly change the world.

Role Description As a Driver Engineer, you'll work on the layer that sits between Modular's compiler and runtime stack and the silicon — the devices, contexts, queues, synchronization primitives, memory allocators, networking, and collectives that every kernel and graph execution depends on. Your work directly affects how reliably and efficiently MAX and Mojo run across NVIDIA, AMD, Apple Silicon, and emerging accelerators, and how cleanly kernel and graph authors can target them from Mojo and Python. This is the team that makes "it just works on a new accelerator" actually true. LOCATION: Candidates based in the US or Canada are welcome to apply. You can work in our office in Los Altos, CA or remotely from home. What you will do - Implement and extend core driver abstractions — Device, Context, Queue, Memory, Function (kernel representation and launch) — across diverse hardware backends, including bindings that expose vendor-specific functionality where it matters. - Contribute to multi-accelerator and multi-node communication and collectives primitives that underpin large-model inference, using technologies like NVLink, RDMA (Infiniband, RoCE, EFA), and sockets — via a combination of direct programming and broker libraries like UCX. - Improve diagnostics and error reporting across our asynchronous execution stack — turning low-level driver failures into actionable messages for kernel and graph authors in production environments. - Partner with peer teams — Kernels, Graph Compiler/Runtime, and Serving — to build and refine the surfaces they consume in the Mojo standard library and MAX framework. - Participate in design discussions, code reviews, and collaborative software development to uphold high engineering standards. - Contribute to a fully open source project — everything you build will be public and part of our GitHub repo. Qualifications - 3+ years of experience writing high-performance, low-latency production systems C++ (modern C++17/20), with strong instincts for ownership, lifetime, ABI stability, concurrency, and parallelism. - Hands-on experience with at least one accelerator driver-level API — CUDA Driver API, HIP, Metal, or Vulkan compute — including streams, events, contexts, and module loading. Familiarity with async allocators and IPC is a plus. - Working understanding of accelerator execution and memory models — stream ordering, host↔device transfers, and pinned memory. Exposure to peer access and multi-GPU topologies (NVLink/xGMI, NUMA) is a plus. - Solid instincts for library and API design — naming, layering, ergonomics. - Strong debugging skills in asynchronous, multi-device systems — GDB/LLDB, sanitizers, CUDA/HIP error modes, race conditions, leaked resources. - A proactive, collaborative mindset, intellectual curiosity, and drive to identify and solve complex technical challenges as part of a high-performing team. Requirements - Experience with asynchronous runtimes, custom memory allocators, or RDMA-based networking (Infiniband, RoCE, EFA, UCX, NIXL, MPI, NVSHMEM/ROCSHMEM/OpenSHMEM) is helpful but not required. - Exposure to non-NVIDIA accelerators in production — AMD ROCm, Apple Metal, etc. - Experience with zero-copy tensor interoperability — DLPack, the CUDA Array Interface, or similar. - Familiarity with Mojo, or recent open-source contributions to systems projects (LLVM, PyTorch, JAX/XLA, TVM, IREE, vLLM, TRT-LLM). - An advanced degree in Computer Science or a related field. Benefits - Amazing Team: We are a progressive and agile team with some of the industry’s best engineering and product leaders. - World-class Benefits: Premier insurance plans, up to 5% 401k matching, flexible paid time off, and more are available to you! - Competitive Compensation: We offer very strong compensation packages, including stock options. - Team Building Events: We organize regular team onsites and local meetups in Los Altos, CA as well as different cities. Traveling 2-4 times a year is expected for all roles. The estimated base salary range for this role to be performed in the US, regardless of the state, is $167,000.00 - $286,000.00 USD. The estimated base salary range for this role to be performed in Canada, regardless of the province, is $158,000.00 - $270,000.00 CAD. The salary for the successful applicant will depend on a variety of permissible, non-discriminatory job-related factors, which include but are not limited to education, training, work experience, business needs, or market demands. This range may be modified in the future. The total compensation for a candidate will also include annual target bonus, equity, and benefits, with equity making up a significant portion of your total compensation. For candidates who fall outside of the listed requirements, we nevertheless encourage you to apply as we may have openings that are lower/higher level than the ones advertised.

Role Description The graph compiler is a central piece of MAX, which executes ML models at state-of-the-art performance across multiple hardware platforms. It is built on MLIR from the ground up using a novel design based on tight integration with the Mojo programming language. Modular’s compiler stack is vertically integrated, from ML serving layer, through the Python API, down to highly tuned kernel implementations - opening up opportunities for optimization not available in competing technologies. This role involves extending and developing the graph compiler to support state-of-the-art features and hardware platforms. You will improve the performance and usability of the graph compiler, creating a joyful developer experience. Modular’s vertically integrated ML serving stack allows you to solve a uniquely diverse set of problems, like heterogeneous compilation, kernel fusions, and distributed model execution. LOCATION: Candidates based in the US or Canada are welcome to apply. You can work in our office in Los Altos, CA or remotely from home. Onboarding for new hires is conducted in-person at headquarters in Los Altos, CA. What you will do: - Design and develop compiler optimizations to improve inference efficiency across CPUs, GPUs, and ML accelerators, including kernel fusion, memory planning, and shape optimization. - Compile large-scale application workloads onto heterogeneous hardware: map hardware-agnostic graphs of computational operators onto hardware-specific graphs of devices and nodes. - Collaborate with the kernels, serving, and Mojo compiler teams to implement core technologies that deliver end-to-end performance across a variety of heterogeneous hardware platforms. - Write design documents for new features and drive for alignment on designs with cross-functional teams. - Collaborate with the customer success team and engage with customers to understand their performance requirements and use cases. Qualifications - 5+ years of software engineering experience. - Proficiency in C++. - Experience working with compilers for machine learning frameworks. - Creativity and curiosity for solving complex problems, a team-oriented attitude that enables you to work well with others. Requirements - Knowledge of and experience working with MLIR and LLVM (helpful but not required). - Experience with ML parallel / distributed programming, heterogeneous ML computation, and/or code generation (helpful but not required). - Knowledge of basic ML implementation and modeling techniques and familiarity with ML frameworks like PyTorch, JAX, or TensorFlow (helpful but not required). Benefits - Amazing Team: We are a progressive and agile team with some of the industry’s best engineering and product leaders. - World-class Benefits: Premier insurance plans, up to 5% 401k matching, flexible paid time off, and more are available to you! - Competitive Compensation: We offer very strong compensation packages, including stock options. - Team Building Events: We organize regular team onsites and local meetups in Los Altos, CA as well as different cities. Traveling 2-4 times a year is expected for all roles. Company Description Working at Modular will enable you to grow quickly as you work alongside incredibly motivated and talented people who have high standards, possess a growth mindset, and a purpose to truly change the world. The estimated base salary range for this role to be performed in the US, regardless of the state, is $198,000.00 - $286,000.00 USD. The estimated base salary range for this role to be performed in Canada, regardless of the province, is $194,000.00 - $280,000.00 CAD. The salary for the successful applicant will depend on a variety of permissible, non-discriminatory job-related factors, which include but are not limited to education, training, work experience, business needs, or market demands. This range may be modified in the future. The total compensation for a candidate will also include annual target bonus, equity, and benefits, with equity making up a significant portion of your total compensation. For candidates who fall outside of the listed requirements, we nevertheless encourage you to apply as we may have openings that are lower/higher level than the ones advertised.

Title: Head of MAX Location: United States of America Fully Remote Permanent Contract Salary: $261K–$363K Experience: 10+ years Department: Healthcare Job Description: - AI developers and researchers today face significant friction in taking trained models into deployment across different types of hardware - They work in a highly fragmented space, with incomplete and patchwork solutions that require integration of many open source components that often times work for one HW vendor but not the other - At Modular, we are building the next generation AI platform that will radically improve the way developers build and deploy AI models - A core part of this offering is MAX - a modern AI inference solution built on the portable Mojo platform for heterogeneous AI acceleration - The Modular platform allows customers to achieve state-of-the-art performance across model families and hardware types - As the leader of the high-caliber MAX team, you will manage an engineering organization specializing in a state of the art inference framework, full stack optimizations including SoTA Kernel on latest GPUs and Accelerators, tools that enable developers to better understand performance, serving optimizations for distributed serving, all to enable frontier models - This organization is building MAX as the next generation framework for AI developers, and revolutionizing AI development and research - This is a fantastic opportunity for a leader to help drive the core technology at Modular! - Leadership: Direct the MAX organization, focusing on the development of MAX Serve, MAX Framework, MAX Kernels, and MAX Tools - Team Development: Cultivate and develop a high-performance team culture, fostering individual growth, collaboration, and innovation - Cross-Functional Collaboration: Work closely with Modular’s engineering and product leaders to build a portable differentiated SaaS platform from Kernel to Cloud - Foster an enterprise adoption of MAX for serving and developing the most advanced GenAI models - Assist customers in deploying AI inference solutions with MAX - Technical Oversight: Make strategic architectural decisions that influence the direction of large-scale projects and initiatives - Working at Modular will enable you to grow quickly as you work alongside incredibly motivated and talented people who have high standards, possess a growth mindset, and a purpose to truly change the world Benefits - A variety of fantastic health benefits (health, dental, vision insurance; life insurance etc) are available - A 401k plan with up to 5% match - Free tax advice on Carta - Generous work-from-home stipend of $1500 to help you improve your home office - Unlimited paid time off and flexible work hours

Role Description In the Cloud Inference team, we are focused on building end to end distributed LLM inference deployments and a repeatable, observable, productive, low toil platform for managing these deployments. Our goal is to make inference both the fastest and most scalable while also building an easiest platform for deploying and scaling models for enterprises and developers alike. - Build the multi-cloud, multi-tenant platform powering Modular’s inference services. - Build fault-tolerant, low toil services able to make use of resources in a variety of hardware platforms Clouds (Tier 1 Cloud Providers & neoclouds). - Push the envelope for operational excellence with request-to-kernel observability, multi-cloud deployments, cold-start optimizations, and more. - Build helm charts, kubernetes operators, and more to make a create simple, effective, maintainable deployments. Benefits - A variety of fantastic health benefits (health, dental, vision insurance; life insurance etc) are available. - A 401k plan with up to 5% match. - Free tax advice on Carta. - Generous work-from-home stipend of $1500 to help you improve your home office. - Unlimited paid time off and flexible work hours.

Role Description At Modular, we're on a mission to make AI accessible to everyone. As a Senior Mojo Libraries Engineer, you'll be a technical leader shaping the future of the Mojo programming language and its Standard Library. Mojo combines performance and expressiveness to unlock the full potential of modern hardware for AI, and you'll be one of the senior voices defining where the language goes next. In this role, you'll help shape the evolution of the Mojo Standard Library and shepherd proposals that move the Mojo language forward: - Shape the evolution of the Mojo Standard Library, leading multi-quarter initiatives and helping set the bar for API design, performance, and ergonomics. - Author and shepherd Mojo language proposals, evaluating tradeoffs against precedent in C++, Rust, Swift, and Python. - Act as a force multiplier across the engineering organization — mentoring senior engineers, raising the bar in design reviews, and unblocking complex technical problems that span team boundaries. - Build alignment across compiler, kernel, runtime, and product teams on library architecture, the broader platform roadmap, and customer commitments. - Own the hardest problems: deep performance work, novel abstractions for emerging hardware, and foundational design decisions that compound over years. - Represent Modular externally — engaging the open source community on GitHub, supporting and reviewing high-quality contributions, and participating in technical discussions. - Stay ahead of the field, tracking Python PEPs, Rust RFCs, C++ proposals, and academic work in systems and compilers. Qualifications - 10+ years of industry experience building production systems software, with deep expertise in modern systems languages such as C++, Rust, or Swift. - A track record of technical leadership in environments with strong technical voices. - Demonstrated experience designing language features, standard library APIs, or core abstractions that have shipped to real users at scale. - Deep expertise in performance engineering, low-level programming, and memory management. - Substantial open source experience — public artifacts that demonstrate your design judgment and ability to collaborate in the open. - A collaborative, high-trust working style and strong alignment with Modular's cultural values. Requirements - GPU programming experience — authoring high-performance compute kernels, designing GPU abstractions, or contributing to GPU-focused languages or libraries. - Prior experience contributing to a programming language, compiler, or standard library project. - Experience participating in language or library standards bodies or comparable experience driving consensus across organizations. - Hands-on experience with Mojo, including accepted contributions to the Standard Library. - Experience working closely with compiler teams on language/library co-design. - An advanced degree in Computer Science or a related field. Benefits - Amazing Team — a progressive and agile team with some of the industry’s best engineering and product leaders. - World-class Benefits — premier insurance plans, up to 5% 401k matching, flexible paid time off, and more. - Competitive Compensation — very strong compensation packages, including stock options. - Team Building Events — regular team onsites and local meetups in various cities. - Growth Opportunities — work alongside incredibly motivated and talented people with high standards and a growth mindset.

About the role: Modular is building a next-generation AI infrastructure platform that unifies fragmented application frameworks and hardware backends into a single programmable system – enabling true compute portability and performance differentiation across the AI stack. We are hiring a Hardware Partnerships BD Lead to define and scale Modular’s hardware ecosystem strategy. This role sits at the intersection of business development, strategy, and technical coordination. You will work directly with Modular’s founders and technical leadership to cultivate deep relationships with leading hardware vendors (GPUs, TPUs, ASICs, emerging accelerators), shape long-term partnership economics, and help architect an open hardware ecosystem around MAX and Mojo. This is not a traditional BD role focused purely on closing transactions. It is a strategic, operational, and relationship-intensive role designed to ensure Modular becomes the programmable software layer for next-generation AI hardware. LOCATION: Candidates based in the United States are welcome to apply. You can work in our office in Los Altos, CA or remotely from home. Onboarding for new hires is conducted in-person in our Los Altos, CA office. What you will do: - Drive and manage relationships with major hardware vendors (e.g., NVIDIA, AMD, Qualcomm, Google, AWS, and emerging accelerator startups), working alongside Modular’s technical and product leadership. - Cultivate early-stage relationships well ahead of formal engineering engagements, identifying long-term strategic alignment and ecosystem opportunities. - Develop scalable partnership models that align incentives between Modular and hardware partners. - Support partnership economics, including business modeling, negotiation support, and commercial structure development. - Help define and execute Modular’s “open hardware” ecosystem strategy in conjunction with the continued maturation of MAX and Mojo. - Design frameworks that allow hardware companies to innovate freely on top of MAX and Mojo while ensuring Modular retains platform control and economic participation. - Contribute to planning and executing major ecosystem launches aligned with industry and company events (e.g., ModCon). - Drive alignment across engineering, legal, product, and business leaders – ensuring continuity and alignment across all stakeholder groups. What you bring to the table: - 10+ years of experience in business development, partnerships, product strategy, or a related function within the hardware, semiconductor, or AI infrastructure ecosystem. - Experience working at a large hardware company (e.g., semiconductor, accelerator, or systems vendor) at a moderately senior level, with a strong understanding of internal stakeholder dynamics and incentive structures. - Demonstrated ability to operate in ambiguous, fast-moving startup environments. - Strong technical literacy in AI infrastructure (e.g., GPUs, TPUs, compilers, ML systems) sufficient to engage credibly with engineering leaders. - Experience structuring and supporting complex commercial agreements. - Excellent written and verbal communication skills, particularly in executive-level and cross-functional settings. - Ability to operate as a senior individual contributor (IC) while collaborating closely with founders and executive leadership. Helpful, but not required: - Prior experience building or participating in industry consortia, open ecosystems, or platform governance structures. - Existing network within hardware startups or major accelerator vendors. - Exposure to open-source platform strategy (e.g., PyTorch-style ecosystem growth). - Familiarity with AI compilers, runtime systems, or performance-sensitive ML workloads What Modular brings to the table: - Amazing Team. We are a progressive and agile team with some of the industry’s best engineering and product leaders. - World-class Benefits. In order to attract the best, we need to offer the best. Premier insurance plans, up to 5% 401k matching, flexible paid time off, and more are available to you! Please note that specific benefit packages may vary based on your location. - Competitive Compensation. We offer very strong compensation packages, including stock options. We want people to be focused on their best work and believe in tailoring compensation plans to meet the needs of our workforce. - Team Building Events. We organize regular team onsites and local meetups in Los Altos, CA as well as different cities. Traveling 2-4 times a year is expected for all roles. Working at Modular will enable you to grow quickly as you work alongside incredibly motivated and talented people who have high standards, possess a growth mindset, and a purpose to truly change the world. The estimated base salary range for this role to be performed in the US, regardless of the state, is $270,000.00 - $375,000.00 USD. The salary for the successful applicant will depend on a variety of permissible, non-discriminatory job-related factors, which include but are not limited to education, training, work experience, business needs, or market demands. This range may be modified in the future. The total compensation for a candidate will also include annual target bonus, equity, and benefits, with equity making up a significant portion of your total compensation. For candidates who fall outside of the listed requirements, we nevertheless encourage you to apply as we may have openings that are lower/higher level than the ones advertised.