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Staff Ai Designer Jobs

7,417 active opportunities · Updated for October 2026

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Explore current staff ai designer jobs. Use filters to narrow by work mode, employment type, experience and date posted.

C
Cohere
📍 Toronto• Full-time• Remote
1mo ago

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! About the Role Cohere builds frontier AI for the enterprise. We're hiring a Senior Director of Integrated Marketing to bring our demand engine, product marketing, and field/partner motion under one strategic roof. This is the senior marketing leader most accountable for pipeline. You're the person who turns Cohere's product, brand, and category narrative into qualified enterprise opportunities for our sales team. Sub-functions report to you: Product Marketing, Web Marketing, Growth, and Events & Partnerships. You'll work with the Chief of Staff on planning, budget, and operating cadence, and with the Marketing Operations Director and her analytics team on attribution, forecasting, martech, and the dashboards your pipeline number lives in. The demand engine only runs if you and the analytics group work as one team on measurement, and building that partnership is part of the job from week one. This role is built for someone who has done it before at a high-growth B2B SaaS or infrastructure company, and is ready to do it again at the frontier of AI. What You'll Run Integrated marketing strategy Build and run the integrated mark

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C
Cohere
📍 Canada• Full-time• Remote• C$285K – C$340K/yr
1mo ago

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 team? The internal infrastructure team is responsible for building world-class infrastructure and tools used to train, evaluate and serve Cohere's foundational models. By joining our team, you will work in close collaboration with AI researchers to support their AI workload needs on the cutting edge, with a strong focus on stability, scalability, and observability. You will be responsible for building and operating superclusters across multiple clouds. Your work will directly accelerate the development of industry-leading AI models that power Cohere's platform North. Please Note: All of our infrastructure roles require participating in a 24x7 on-call rotation, where you are compensated for your on-call schedule. As a Staff Software Engineer, you will: Build and scale ML-optimized HPC infrastructure : Deploy and manage Kubernetes-based GPU/TPU superclusters across multiple clouds, ensuring high throughput and low-latency performance for AI workloads. Optimize for AI/ML training : Collaborate with cloud providers to fine-tune infrastructure for cost efficiency, reliability, and performance , leveraging technologies like R

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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 team? The internal infrastructure team is responsible for building world-class infrastructure and tools used to train, evaluate and serve Cohere's foundational models. By joining our team, you will work in close collaboration with AI researchers to support their AI workload needs on the cutting edge, with a strong focus on stability, scalability, and observability. You will be responsible for building and operating superclusters across multiple clouds. Your work will directly accelerate the development of industry-leading AI models that power Cohere's platform North. Please Note: All of our infrastructure roles require participating in a 24x7 on-call rotation, where you are compensated for your on-call schedule. As a Staff Software Engineer, you will: Build and scale ML-optimized HPC infrastructure : Deploy and manage Kubernetes-based GPU/TPU superclusters across multiple clouds, ensuring high throughput and low-latency performance for AI workloads. Optimize for AI/ML training : Collaborate with cloud providers to fine-tune infrastructure for cost efficiency, reliability, and performance , leveraging technologies like R

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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. About the Role We are looking for Staff System Software Engineer in Test to join our team. In this role, you will be responsible for design, development, automation and reporting of Integration and system tests spanning across firmware and device drivers. This role requires you to have significant technical breadth and deep understanding of low-level system software specifically in server class systems. You will be part of a new team responsible for integration of different system software deliverables and development of system tests spanning all the components. You will contribute to shaping the test strategy , guide best practices and solve complex problems while maintaining a strong hands-on focus. You will partner with development and other QA teams to deliver high quality scalable and reliable solutions. About the Team Integration and system test team is responsible for verification and validation of integrated components across Board management controller (BMC), Firmware and Linux device driver. The team is also responsible for management and maintenance of common tools and pipel

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C
Cohere
📍 Canada• Internship• Remote
5mo ago

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? Ship state of the art models to production. Design and implement novel research ideas. Build elegant training/deployment pipelines. Join us at a pivotal moment, shape what we build and wear multiple hats as an intern! Our recruitment process will begin in the upcoming weeks, and we will be carefully reviewing applications and assessing potential candidates for our internships. Should we find a suitable match with your qualifications and our requirements, we will be in touch to discuss the opportunity further and to advance your application to the next stage Please Note: To be eligible for this position you should be a student currently enrolled in a post-secondary program, available for a full-time 3-6 month internship, co-op, or research work term. As a Machine Learning Intern, you will: Design, train and improve upon cutting-edge models. Help us develop new techniques to train and serve models safer, better, and faster. Train extremely large-scale models on massive datasets. Explore continual and active learning strategies for streaming data. Learn from experienced senior machine learning technical staff. Work c

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Nextdoor
📍 Us Remote• Full-time• Remote
43mo ago

#Team Nextdoor Nextdoor (NYSE: NXDR) is the essential neighborhood network. Neighbors, public agencies, and businesses use Nextdoor to connect around local information that matters in more than 350,000 neighborhoods across 11 countries. Nextdoor builds innovative technology to foster local community, share important news, and create neighborhood connections at scale. Download the app and join the neighborhood at nextdoor.com . Meet Your Future Neighbors As a Senior or Staff Software Engineer at Nextdoor, you’ll join a focused team of developers, product managers, and designers who are passionate about using technology to cultivate a kinder world where everyone has a neighbor they can rely on. We are a small, high performing team of engineers that wear multiple hats and prioritize impact for our customers. We care about moving fast and delivering impact, without compromising on quality and reliability as guided by our Engineering Principles . You will have the opportunity to learn from your co-workers and teach them. As a team, we will make each other better and build great software. At Nextdoor, we operate in an AI-first environment and expect every team member to actively use AI tools as part of their workflow. We aren't looking for prompt engineers; we’re looking for people who use tools like Claude, Gemini, ChatGPT, and Glean to challenge their own thinking and take full ownership of AI-assisted outputs. We also offer a warm and inclusive work environment that embraces a hybrid employment model, blending an in office presence and work from home experience for our valued employees. The hiring team will go over these expectations with you if you are being considered for a role near one of our offices in San Francisco, Los Angeles, Chicago, Dallas, New York, and London. The Impact You’ll Make We believe in empowering our teams to own all aspects of bringing Nextdoor to life. As such, you’ll get the opportunity to make key contributions across our enginee

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Toast
📍 United States• Remote• $230K – $368K/yr
Just now

Toast creates technology to help restaurants and local businesses succeed in a digital world, helping business owners operate, increase sales, engage customers, and keep employees happy. We help restaurants streamline operations, increase revenue, and deliver amazing guest experiences through our platform that combines restaurant point of sale, team management, guest-facing technology, and award-winning customer support. As a Toaster, you will be challenged to take on meaningful projects to help craft the company's future. Join us as we empower the restaurant community to delight guests, do what they love, and thrive. Your mission is to lead the architectural design, technical execution, and implementation across the foundational domains of Toast’s Team Suite products, Payroll and Team Management. The Payroll product delivers daily value to its users - enabling restaurant owners to pay their staff and pay their taxes, and enabling transparency for wages and tips for restaurant employees. The Team Management suite allows restaurants to hire, manage, and schedule their staff. As a Principal Engineer, you will serve as a key technical leader in the group, driving modern architectural patterns—including spec-driven development and agentic workflows—to deliver high-impact software. A day in the life (Responsibilities) Lead fellow developers, product managers, designers, and user researchers to build a strong tech infrastructure that enables amazing features Own the architecture for authentication, authorization, and organizational hierarchy — driving technical direction in these domains across the organization Help us transform a traditional SasS platform into an agentic, system-of-action Flex your full-stack muscles by driving challenging large end-to-end initiatives or core architecture changes in a supportive, collaborative team environment Define and drive technical strategy for problems that affect multiple parts of the business Mentor developers across multip

REMOTEjavareactai
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About the role Scale's Global Public Sector team is focused on using AI to address critical challenges facing the public sector around the world. As a Staff Applied AI Engineer, you'll raise the bar for how AI gets built, governed, and evaluated across the team. You'll define standards that other engineers adopt, such as evaluation methodologies for agents and MLOps practices, while acting as the senior technical voice for the most sensitive AI decisions our clients face. What you'll do Define standards for responsible AI, model governance, and production MLOps that get adopted broadly across the Global Public Sector team Build or validate the highest-risk parts of strategic AI systems and use those systems to establish standards other teams can adopt. Architect AI systems designed to prevent systemic failure, and lead the resolution of the most severe incidents tied to model safety or data integrity Build reusable AI capabilities, such as production-ready agent implementations built on proven architectures, fine-tuned models, or evaluation methodologies, that other engineers and clients can build on Advise on which new AI developments are worth adopting, and help set the technical roadmap for the domain Act as the senior technical partner to client leadership on AI strategy Coach Senior Applied AI Engineers, delegate ownership of technical domains, and build systems and practices that enable multiple teams to deliver safer AI Contribute to recruiting and representing Scale's AI work externally What we look for 7+ years of engineering experience, with a multi-year track record owning AI/ML systems in production Experience judging the quality of training data, selecting the right adaptation method for a given model, evaluating fine-tuning results, and balancing serving cost, latency, and quality trade-offs Experience owning an AI-powered product end to end, including direct involvement in the AI's behaviour rather than implementing ML work scoped by another team A tr

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Hark
📍 San Jose• $180K – $450K/yr
8 days ago

About Hark Hark is an artificial intelligence company building advanced, personalized intelligence. One that is proactive, multimodal, and capable of interacting with the world through speech, text, vision, and persistent memory. We're pairing that intelligence with next-generation hardware to create a universal interface between humans and machines. While today's AI largely operates through chat boxes and decade-old devices, Hark is focused on what comes next: agentic systems that interact naturally with people and the real world. To get there, we're developing multimodal models and next-generation AI hardware together - designed from the ground up as a single, unified interface for a new era of intelligent systems. About the Role The Omni team at Hark is building the next generation of AI experiences beyond text, enabling models to understand and generate content across multiple modalities, including text, audio, and vision. Our goal is to create seamless, real-time multimodal intelligence that powers intuitive and immersive user experiences. We're looking for an engineer who sits at the intersection of model research and production systems. Together with our researchers, you'll decide what "better" means for a model and how to prove it — then build the infrastructure that makes those proofs reliable and repeatable: evaluation harnesses, data pipelines, and model training that hold up at scale and that the whole team can build on. This is a hands-on, individual-contributor position. The systems that judge whether a model improved, and the environments that drive that improvement, will be yours. Responsibilities Build and own end-to-end evaluation suites for LLM capabilities: task specs, grading logic, and the dashboards researchers check every day. Run the eval harness as a production service — sandboxed execution, tool calling, multi-turn and agentic tasks, deterministic replay, and caching — so a full evaluation pass is cheap and gives the same answer twic

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Hark
📍 San Jose• $180K – $450K/yr
7mo ago

About Hark Hark is an artificial intelligence company building advanced, personalized intelligence. One that is proactive, multimodal, and capable of interacting with the world through speech, text, vision, and persistent memory. We're pairing that intelligence with next-generation hardware to create a universal interface between humans and machines. While today's AI largely operates through chat boxes and decade-old devices, Hark is focused on what comes next: agentic systems that interact naturally with people and the real world. To get there, we're developing multimodal models and next-generation AI hardware together - designed from the ground up as a single, unified interface for a new era of intelligent systems. About the Role The Omni team at Hark is building the next generation of AI experiences beyond text, enabling models to understand and generate content across multiple modalities, including text, audio. Our goal is to create seamless, real-time multimodal intelligence that powers intuitive and immersive user experiences. As part of the Omni team, you will drive the development of advanced speech and audio capabilities within multimodal foundation models. You will work across the full stack—from data and modeling to training, evaluation, and real-time serving—pushing the boundaries of speech intelligence and human-computer interaction. Responsibilities Drive research and development to advance speech and audio capabilities in multimodal models, including speech recognition, synthesis, and understanding. Develop and improve large-scale speech and audio data pipelines, including data collection, filtering, alignment, and synthetic data generation. Design and implement state-of-the-art models for speech and audio, including end-to-end multimodal architectures and real-time systems. Build evaluation frameworks and internal benchmarks to measure speech quality, latency, robustness, and overall user experience. Optimize models and systems for real-time pe

machine learningartificial intelligenceai
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Hark
📍 San Jose• $180K – $450K/yr
7mo ago

About Hark Hark is an artificial intelligence company building advanced, personalized intelligence. One that is proactive, multimodal, and capable of interacting with the world through speech, text, vision, and persistent memory. We're pairing that intelligence with next-generation hardware to create a universal interface between humans and machines. While today's AI largely operates through chat boxes and decade-old devices, Hark is focused on what comes next: agentic systems that interact naturally with people and the real world. To get there, we're developing multimodal models and next-generation AI hardware together - designed from the ground up as a single, unified interface for a new era of intelligent systems. About the Role The Omni team at Hark is building the next generation of AI experiences beyond text, enabling models to understand and generate content across multiple modalities, including text, audio, and vision. Our goal is to create seamless, real-time multimodal intelligence that powers intuitive and immersive user experiences. As part of the Omni team, you will focus on developing large-scale pretraining systems and foundation models. This includes working across the full stack—from data curation and large-scale training infrastructure to model architecture and optimization. You will play a key role in advancing the core capabilities of our models through pretraining at scale. Responsibilities Drive research and development in large-scale LLM and multimodal pretraining, focusing on improving model capability through better data, scaling, and architecture. Develop and optimize data pipelines for pretraining, including large-scale data curation, filtering, deduplication, and synthetic data generation. Design and implement efficient training strategies for foundation models, including distributed training, scaling laws, and optimization techniques. Build and improve pretraining infrastructure, including training systems, data pipelines, and comp

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7mo ago

About Hark Hark is an artificial intelligence company building advanced, personalized intelligence. One that is proactive, multimodal, and capable of interacting with the world through speech, text, vision, and persistent memory. We're pairing that intelligence with next-generation hardware to create a universal interface between humans and machines. While today's AI largely operates through chat boxes and decade-old devices, Hark is focused on what comes next: agentic systems that interact naturally with people and the real world. To get there, we're developing multimodal models and next-generation AI hardware together - designed from the ground up as a single, unified interface for a new era of intelligent systems. About the Role The Omni team at Hark is building the next generation of AI experiences beyond text, enabling models to understand and generate content across multiple modalities, including text, audio, and vision. Our goal is to create seamless, real-time multimodal intelligence that powers intuitive and immersive user experiences. As part of the Omni team, you will help drive the development of real-time audio, video, and multimodal models. This includes working across the full stack—from data and modeling to training, serving, and product integration. You will contribute to both pretraining and posttraining efforts while collaborating closely with product teams to push the boundaries of model capability and deliver exceptional end-to-end user experiences. Responsibilities Design and implement efficient RL algorithms and training strategies to achieve state-of-the-art performance in multimodal foundation models, PPO/GRPO/RLHF Drive research and development agendas to advance real-time multimodal intelligence, including audio, video modeling capabilities. Improve data quality for large-scale post training by developing data filtering, curation, and synthetic data generation techniques. Build evaluation frameworks and internal benchmarks to m

machine learningartificial intelligenceai
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Hark
📍 San Jose• $180K – $450K/yr
7mo ago

About Hark Hark is an artificial intelligence company building advanced, personalized intelligence. One that is proactive, multimodal, and capable of interacting with the world through speech, text, vision, and persistent memory. We're pairing that intelligence with next-generation hardware to create a universal interface between humans and machines. While today's AI largely operates through chat boxes and decade-old devices, Hark is focused on what comes next: agentic systems that interact naturally with people and the real world. To get there, we're developing multimodal models and next-generation AI hardware together - designed from the ground up as a single, unified interface for a new era of intelligent systems. About the Role The Omni team at Hark is building the next generation of AI experiences beyond text, enabling models to understand and generate content across multiple modalities, including text, and vision. Our goal is to create seamless, real-time multimodal intelligence that powers intuitive and immersive user experiences. As part of the Omni team, you will help drive the development of real-time audio, video, and multimodal world models. This includes working across the full stack—from data and modeling to training, serving, and product integration. You will contribute to both pretraining and posttraining efforts while collaborating closely with product teams to push the boundaries of model capability and deliver exceptional end-to-end user experiences. Responsibilities Drive research and development agendas to advance real-time multimodal intelligence, including audio, video, and world modeling capabilities. Improve data quality for large-scale multimodal training by developing data filtering, curation, and synthetic data generation techniques. Build evaluation frameworks and internal benchmarks to measure model capability, reliability, and user experience across modalities. Design and implement efficient algorithms and training strategi

machine learningartificial intelligenceai
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Hark
📍 San Jose• $180K – $450K/yr
7mo ago

About Hark Hark is an artificial intelligence company building advanced, personalized intelligence. One that is proactive, multimodal, and capable of interacting with the world through speech, text, vision, and persistent memory. We're pairing that intelligence with next-generation hardware to create a universal interface between humans and machines. While today's AI largely operates through chat boxes and decade-old devices, Hark is focused on what comes next: agentic systems that interact naturally with people and the real world. To get there, we're developing multimodal models and next-generation AI hardware together - designed from the ground up as a single, unified interface for a new era of intelligent systems. About the Role The Omni team at Hark is building the next generation of AI experiences beyond text, enabling models to understand and generate content across multiple modalities, including text, and vision. Our goal is to create seamless, real-time multimodal intelligence that powers intuitive and immersive user experiences. As part of the Omni team, you will help drive the development of text, video, and multimodal models. This includes working across the full stack—from data and modeling to training, serving, and product integration. You will contribute to both pretraining and posttraining efforts while collaborating closely with product teams to push the boundaries of model capability and deliver exceptional end-to-end user experiences. Responsibilities Drive mid-training and post-training research for multimodal foundation models — continued/mid-training on large-scale interleaved vision-text and video-audio corpora, supervised fine-tuning, and reinforcement learning to advance image, video, and video-audio understanding. Own the RL stack for multimodal post-training: reward modeling, preference optimization and RLVR-style verifiable rewards, policy optimization (PPO / GRPO / DPO and variants), rollout and sampling strategies, and mitigation o

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21 days ago

About Hark Hark is an artificial intelligence company building advanced, personalized intelligence. One that is proactive, multimodal, and capable of interacting with the world through speech, text, vision, and persistent memory. We're pairing that intelligence with next-generation hardware to create a universal interface between humans and machines. While today's AI largely operates through chat boxes and decade-old devices, Hark is focused on what comes next: agentic systems that interact naturally with people and the real world. To get there, we're developing multimodal models and next-generation AI hardware together - designed from the ground up as a single, unified interface for a new era of intelligent systems. About the Role At Hark, you'll lead the development for the foundation of agentic reinforcement learning (RL) environments: the digital worlds in which AI agents learn to use software, navigate complex workflows, and act on their surroundings. Our ambition is to simulate the breadth and complexity of the internet, connecting websites, apps, services, and artifacts into rich, stateful environments, with the potential to evolve dynamically over time. This is a chance to shape both the worlds agents learn in and the systems that make learning at scale possible. You'll build environments end-to-end and work closely with researchers to bring them into RL training and evaluation. You'll also develop the infrastructure behind our agent gym, making these environments easy to integrate, reproduce, and scale across heterogeneous execution targets. Responsibilities Build agent environments and simulations end-to-end, including frontend interfaces, backend services, APIs, data models, tools, and realistic workflows used to train and evaluate AI agents. Build the infrastructure that powers our agent gym, including orchestration, sandboxing, packaging, benchmarking, and systems for running environments across heterogeneous targets. Create interconnected simulations w

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