Staff Silicon Verification Engineer in New York

The Chief of Staff is a high-visibility leadership role responsible for the operational success of the SVP, General Manager’s organization. Acting as a strategic partner, you will ensure the business operates at peak velocity by driving key initiatives, improving organizational effectiveness, and aligning teams around strategic priorities. You will translate high-level goals into clear execution plans across the business, providing clarity in a fast-paced, complex environment. This role is designed for a seasoned operator who excels at driving accountability among senior leaders and building the systems necessary to scale a SaaS business. You will identify operational gaps, mitigate risks before they impact the bottom line, and act as an extension of leadership—prioritizing, executing, and communicating critical projects to enable the executive team to operate at maximum efficiency. ** Please note that this opportunity is located in New York, NY, and requires this hire to work from our office 4 days a week. ** As a Chief of Staff You Can Expect: Drive the Operating Cadence: Design and manage the GM's leadership meetings, QBRs, and planning cycles to keep the team aligned and hitting KPIs. Force Execution: Partner with Sales, Customer Success, Account Management, Implementation, Product leaders to unblock projects and hold senior stakeholders accountable for deliverables. Own Plan Integrity: Keep the team aligned to the quarterly and annual plan, hold leaders accountable for the commitments behind it, and flag risk early, before it shows up as a miss in the business review. Drive Alignment & Follow-Through: Ensure decisions and commitments made in leadership meetings are clearly communicated across the team, tracked to completion, and actually followed through on, closing the loop between what was decided and what gets done. Prioritize Ruthlessly: Act as a surrogate for the GM in high-level meetings, surfacing critical risks early and filtering out noise to focus

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We are looking for a strong technical lead to guide the engineers designing, building, and maintaining the novel, high-performance systems that make up our serverless platform. You'll lead the team responsible for Modal's machines layer: the fleet of bare metal and cloud hosts that every Function, Sandbox, and training job runs on, and the control plane that provisions, images, monitors, and repairs them. You'll own the full lifecycle of a machine, from accepting and benchmarking new hardware from a growing set of providers, to network bring-up, kernel and image management, GPU and disk health tracking, and automated remediation of unhealthy hosts. You'll manage a team of 3–8 engineers while staying hands-on across the stack which involves BMCs, firmware, PXE, bootloaders, Linux networking, drivers, and distributed control-plane services, and you'll shape our long-

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. About Modal Design Modal is building the future of serverless computing, and the brand that carries that story is still taking shape — You'll join Modal's newly formed Brand team inside our design org as one of its first senior hires, working directly with the Director of Brand Design and Head of Design to build a brand developers recognize instantly and remember. The Role As a staff-level Brand Designer, you will have major influence over every brand surface: the marketing website, campaigns, events, editorial projects like the GPU Glossary and forthcoming publications, and out-of-home work as we scale into larger formats. You'll also be a beacon to external agencies, representing Modal's internal creative voice and making sure the work translates into a system we can actually build on. And as the studio grows, you'll help set its craft standard — guiding and mentoring earl

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We are looking for strong engineers with experience and interest in designing, building, and maintaining the novel, high-performance systems that make up our serverless platform. Requirements: 5+ years of experience writing high-quality production code Experience building high-performance distributed systems at a large scale (the more battle scars, the better) Strong cloud skills Strong knowledge of low-level operating system foundations (Linux kernel, file systems, containers, etc.) Experience with performance engineering (tell us a story of when you shaved off a few milliseconds!) Ability to work in-person in our NYC or SF office. Prior experience with Rust is nice to have, but not required. Ability to participate in on-call rotation and respond to production incidents.

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: At Modal, we sell cloud services atop which our customers run their critical production systems. As a rapidly growing new cloud infrastructure company, we seek to improve our reliability dramatically while scaling the size of our platform, customer base, and our team. This role is for people who are deep systems thinkers, love stacking nines, and thrive from making others move faster at scale. Responsibilities include: Identifying architectural changes to improve reliability and performance. Fostering a culture of reliability across Modal’s engineering organization. Defining and implementing operational processes such as deployments, upgrades, etc. Operating systems like Kubernetes, Postgres, Redis, etc. Participating in on-call rotations, and responding to production incidents. Requirements: 5+ years of experience writing high-quality production code. 2+ years of

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We are looking for strong engineers with experience in making ML systems performant at scale. If you are interested in contributing to open-source projects and Modal’s container runtime to push language and diffusion models towards higher throughput and lower latency, we’d love to hear from you! Requirements: 5+ years of experience writing high-quality, high-performance code. Experience working with torch, high-level ML frameworks, and inference engines (vLLM or TensorRT). Familiarity with Nvidia GPU architecture and CUDA. Experience with ML performance engineering (tell us a story about boosting GPU performance — debugging SM occupancy issues, rewriting an algorithm to be compute-bound, eliminating host overhead, etc). Nice-to-have: familiarity with low-level operating system foundations (Linux kernel, file systems, containers, etc).

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We're looking for strong backend engineers who love building a developer tools used by the largest AI companies in the world. You’ll be building for things at scale, but also for new AI workflows that change every day. Requirements: Experience building and shipping modern web applications end-to-end. We care more about what you’ve built than how many years you’ve been building. Comfort working across the stack: TypeScript on the frontend, Python services on the backend, and ClickHouse for data and analytics. Deep knowledge of observability tools and patterns used for large-scale workloads such as custom sandboxes, training and inference for large language (LLM) and diffusion models. Experience with at least one of: billing/payments systems, B2B SaaS tooling, or enterprise software, or LLM / diffusion models inference and training loads. Strong product instincts; yo

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We’re looking for strong engineers with experience building developer tools that users love to work with. Our ideal candidate is someone with a demonstrated drive to build beautiful interfaces that enhance developer productivity. Requirements: 5+ years of experience developing high-quality Python libraries with broad user-bases, ideally including some experience maintaining open-source software. Knowledge of advanced Python features, especially async programming. A strong product sense that manifests as a focus on developer ergonomics and productivity. A high level of customer empathy, good communication skills, and an openness to working directly with our users to help solve their problems. Ability to participate in on-call rotation and respond to production incidents. Ability to work in-person in our NYC or Stockholm office. Any of the following would be a plus:

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We're looking for a Growth Engineer to own the technical foundation of Modal's marketing and developer-facing web surfaces: the marketing site, docs site, growth landing pages, high-profile microsites, forms, analytics instrumentation, and the integrations that help users discover, understand, and get started with Modal. This is a frontend-heavy role for someone with strong product taste, web engineering craft, and a business-owner mindset. You'll partner with Product Engineering, Design, Data, and Growth to ship polished, measurable web experiences from high-profile projects like the GPU Glossary and LLM Engine Advisor to internal tooling that helps teams publish content faster. When this role is going well, Modal launches new pages, docs experiences, campaigns, and experiments quickly without sacrificing performance, craft, or measurement. In this role you will:

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: Most of the value of owning a model shows up at serving time. We're building a platform that covers the whole life of an LLM -- train it, deploy it, observe it -- and inference is where teams feel the difference every day. We already run elastic inference, sandboxes, distributed volumes, and multi-node training, and we control the infrastructure underneath, so the serving stack is ours to shape rather than something we resell. You will do hands-on inference research at Modal, working with the research lead to pick high-impact bets and owning them end to end. The bets that matter most are the ones that move cost per token and tail latency on the workloads our customers actually run. What you'll do: Own end-to-end inference research bets: speculative decoding, disaggregated prefill/decode, quantization (FP8, INT4), KV-cache and memory management, autoscaling for spik

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We're building a platform that covers the whole life of an LLM: training it, deploying it, and observing it in production. We already run multi-node training, elastic inference, sandboxes, and distributed volumes, and we control the infrastructure underneath. We’re looking for research depth in post-training to sit alongside our systems and product work. What you'll do: We are looking for research scientists with a strong track record in reinforcement learning, machine learning, and foundation models, including large language and multimodal models, to join our research team. This role is well suited to candidates interested in improving existing methods and developing new techniques for large-scale model training, optimization, and inference, extending models to long-context and long-horizon tasks, and improving inference-time efficiency, reliability, and robustnes

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? Our team is a fast-growing group of researchers and engineers focused on building reliable ML systems and pushing the boundaries of LLM inference efficiency. We develop techniques that improve how models execute in production, driving lower latency, higher throughput, and consistent quality across diverse workloads. As an engineer on this team, you’ll work across the inference stack to improve core performance metrics by diving deep into model execution, identifying bottlenecks, and developing innovative optimizations. You’ll collaborate closely with modeling and systems teams to experiment, measure, and ship improvements that meaningfully accelerate inference. As the team evolves, you’ll have opportunities to build expertise in advanced performance techniques, including GPU/CUDA optimizations, kernel-level improvements, and model execution strategies for MoE and large-scale architectures. Please Note: We have offices in Toronto, Montreal, San Francisco, New York, Paris, Seoul and London. We embrace a remote-friendly environment, and as part of this approach, we strategically distribute teams based on interests, e

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! The Chief of Staff is a strategic leadership role focused on optimizing sales operations, enabling revenue growth, and ensuring alignment between sales execution and company objectives. This exciting career opportunity offers a blend of operational oversight, strategic planning, and cross-functional collaboration. Key Responsibilities Sales Strategy & Execution: Partner with the CRO to define and implement sales strategies, forecasts, and performance metrics. Operational Excellence: Streamline sales processes, including pipeline management, CRM optimization, and sales enablement tools. Cross-Functional Coordination: Work closely with marketing, product, and customer success teams to ensure cohesive go-to-market execution. Performance Analytics: Monitor sales KPIs, conduct data-driven insights, and recommend adjustments to improve conversion rates and revenue attainment. Team Leadership: Contribute to sales operations, business development, and support functions, fostering a high-performance culture. Stakeholder Management: Serve as a liaison between sales leadership and executive teams, ensuring clear communication and strat

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam. Plaid’s Product team builds the network that powers open finance. At Supplier Products, we focus on building trusted, transparent experiences for financial institutions operating in Plaid’s ecosystem. Responsibilities: You will lead a team of 6 engineers, ranging from mid-level to Staff, developing them through clear goal setting, coaching, and feedback. You’ll define and drive the long-term strategy for this focus area, in close partnership with technical and product leaders across Plaid. You’ll collaborate with cross-functional partners to identify high-leverage opportunities, shape the roadmap, and dive deep into technical design and execution details to ensure consistent delivery of high-impact business outcomes. You’ll uphold a high bar for technical quality and delivery velocity, leading by example. Qualifications: 8+ years of industry experience, that includes time as a Staff-level engineer before transitioning into management. 1+ years of engineering management experience Deep experience designing scalable, reliable architectures that support real-world products at scale. Track record of building and growing high performing engineering teams (either as an engineer or a manager). Our mission

The mission of The New York Times is to seek the truth and help people understand the world. That means independent journalism is at the heart of all we do as a company. It’s why we have a world-renowned newsroom that sends journalists to report on the ground from nearly 160 countries. It’s why we focus deeply on how our readers will experience our journalism, from print to audio to a world-class digital and app destination. And it’s why our business strategy centers on making journalism so good that it’s worth paying for. The Role: The New York Times is looking for someone to join our Newsroom Operations team. We are looking for someone who can handle the demands of a fast-paced news environment and can work under sometimes ambiguous circumstances. The Operations Manager will work with Shows and Visuals, but also assist other departments at the center of visual journalism at The Times. The work of these journalists — along with visual efforts across the newsroom — is a pillar of our reporting that has a large and engaged audience. You will help support these journalists with a variety of daily responsibilities and short- and long-term projects and coordinate with this group's other operations managers. You will be responsible for ensuring that day-to-day on-site operational tasks are completed in a timely manner to support the needs of department managers and staff. The Operations Manager's work is critical in supporting the journalism produced at The New York Times and all tasks, whether daily, weekly or one-off are greatly valued. You will report to a senior manager of Newsroom Operations. This role will be Hybrid, with a required in-office presence of 4 days a week. The schedule of these 4 days can fluctuate based on the needs of the desks, and during some peak news cycles, you may be required to be on site for 5 days during those weeks. Responsibilities: Support editors during breaking news and timely news events, ensuring that our journalists have