Staff Technical Writer Jobs

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 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've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. Our team includes creators of popular open-source projects (e.g., Seaborn , Luigi ), 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).

SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where we are not. Today, SpaceX is actively developing the technologies to make this possible, with the ultimate goal of making life multiplanetary and expanding consciousness to the stars. SpaceXSI is building Super Intelligence to help humanity understand the universe. Our teams are building the full Super Intelligence stack: from our Colossus supercomputers, to Grok models, to our suite of applications, including Grok Bot, Grok Build, Grok Imagine, Grok Voice, and X. We're creating a powerful flywheel where more compute trains better models, better models power more useful products, and what we learn from people using those products shapes what we build next. ABOUT THE ROLE: You will join the multimodal team to push toward superhuman multimodal intelligence. Advance understanding and generation across modalities—image, video, audio, and text—spanning the full stack: data curation/acquisition, tokenizer training, large-scale pre-training, post-training/alignment, infrastructure/scaling, evaluation, tooling/demos, and end-to-end product experiences. Collaborate cross-functionally with pre-training, post-training, reasoning, data, applied, and product teams to deliver frontier capabilities in multimodal reasoning, world modeling, tool use, agentic behaviors, and interactive human-AI collaboration. Contribute to building models that can see, hear, reason about, and interact with the world in real time at unprecedented levels. RESPONSIBILITIES: Design, build, and optimize large-scale distributed systems for multimodal pre-training, post-training, inference, data processing, and tokenization at web/petabyte scale. Develop high-throughput pipelines for data acquisition, preprocessing, filtering, generation, decoding, loading, crawling, visualization, and management (images, videos, audio + text). Advance multimodal capabilities including sp

Perplexity serves tens of millions of users daily with reliable, high-quality answers grounded in an LLM-first search engine and specialized data sources. The Answer Quality team ensures that our prompts, tools, search systems, datasets, and models work together to create the best possible experience for our users. As our product and agent capabilities evolve, we need evaluation systems that are fast, reliable, production-faithful, and actionable. In this role, you will build and improve the technical foundations that support Answer Quality across Perplexity. This includes our shared evaluation infrastructure and the platform used to replay and analyze agent traces. You will work closely with data scientists, engineers, and product teams to identify quality problems, measure their impact, and turn evaluation findings into product improvements. Responsibilities Build shared evaluation infrastructure that helps teams run reliable evals, analyze results, and make product and model decisions Develop the platform for replaying and analyzing agent traces to reproduce production behavior and diagnose failures Build and operate scalable systems for processing, storing, and monitoring interaction, trace, and evaluation data Partner with data scientists, engineers, and product teams to turn answer-quality problems into evaluations, analyses, and product improvements Operate in a small, high-impact team where your work directly shapes how Perplexity measures and improves Answer Quality Qualifications 4+ years of software, data, or machine learning engineering experience shipping and operating production systems Strong proficiency in Python and SQL, with solid fundamentals in system design, data modeling, and distributed systems Experience building big-data systems, including distributed compute, large-scale storage, and high-volume pipelines Demonstrated ownership of ambiguous technical projects from initial design through production operation Ability to work effectively with

We are looking for an AI Infra engineer to join our growing team. We work with Kubernetes, Slurm, Python, C++, PyTorch, and primarily on AWS. As an AI Infrastructure Engineer, you will be partnering closely with our Inference and Research teams to build, deploy, and optimize our large-scale AI training and inference clusters. Responsibilities Design, deploy, and maintain scalable Kubernetes clusters for AI model inference and training workloads Manage and optimize Slurm-based HPC environments for distributed training of large language models Develop robust APIs and orchestration systems for both training pipelines and inference services Implement resource scheduling and job management systems across heterogeneous compute environments Benchmark system performance, diagnose bottlenecks, and implement improvements across both training and inference infrastructure Build monitoring, alerting, and observability solutions tailored to ML workloads running on Kubernetes and Slurm Respond swiftly to system outages and collaborate across teams to maintain high uptime for critical training runs and inference services Optimize cluster utilization and implement autoscaling strategies for dynamic workload demands Qualifications Strong expertise in Kubernetes administration, including custom resource definitions, operators, and cluster management Hands-on experience with Slurm workload management, including job scheduling, resource allocation, and cluster optimization Experience with deploying and managing distributed training systems at scale Deep understanding of container orchestration and distributed systems architecture High level familiarity with LLM architecture and training processes (Multi-Head Attention, Multi/Grouped-Query, distributed training strategies) Experience managing GPU clusters and optimizing compute resource utilization Required Skills Expert-level Kubernetes administration and YAML configuration management Proficiency with Slurm job scheduling, resource mana

We are looking for an AI Infra engineer to join our growing team. We work with Kubernetes, Slurm, Python, C++, PyTorch, and primarily on AWS. As an AI Infrastructure Engineer, you will be partnering closely with our Inference and Research teams to build, deploy, and optimize our large-scale AI training and inference clusters Responsibilities Design, deploy, and maintain scalable Kubernetes clusters for AI model inference and training workloads Manage and optimize Slurm-based HPC environments for distributed training of large language models Develop robust APIs and orchestration systems for both training pipelines and inference services Implement resource scheduling and job management systems across heterogeneous compute environments Benchmark system performance, diagnose bottlenecks, and implement improvements across both training and inference infrastructure Build monitoring, alerting, and observability solutions tailored to ML workloads running on Kubernetes and Slurm Respond swiftly to system outages and collaborate across teams to maintain high uptime for critical training runs and inference services Optimize cluster utilization and implement autoscaling strategies for dynamic workload demands Qualifications Strong expertise in Kubernetes administration, including custom resource definitions, operators, and cluster management Hands-on experience with Slurm workload management, including job scheduling, resource allocation, and cluster optimization Experience with deploying and managing distributed training systems at scale Deep understanding of container orchestration and distributed systems architecture High level familiarity with LLM architecture and training processes (Multi-Head Attention, Multi/Grouped-Query, distributed training strategies) Experience managing GPU clusters and optimizing compute resource utilization Required Skills Expert-level Kubernetes administration and YAML configuration management Proficiency with Slurm job scheduling, resource manag

Our vision is to transform how the world uses information to enrich life for all. Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing. Our vision is to transform how the world uses information to enrich life for all. Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Position Overview The Member of Technical Staff (MTS) in Process Development for Advanced Thin Film plays a critical role in advancing thin film process development for NAND memory technology. This position is responsible for performing experiments, conducting material characterization, and providing support for process integration and fixing. As a key contributor, the MTS collaborates with senior engineers and Multi-functional teams to promote manufacturability, continuous improvement, and ongoing technology advancement within the organization. Key Responsibilities</span

Perplexity is seeking a highly skilled, experienced and hands-on Offensive Security Engineer to join our dynamic security team, taking an adversarial approach to hardening Perplexity's infrastructure, applications, and AI systems. You'll plan and execute red team operations, penetration tests, and attack simulations across our cloud infrastructure, web and mobile applications, AI/ML pipeline, and corporate environment—finding real vulnerabilities before adversaries do and working directly with engineering teams to drive remediation. Responsibilities Plan and execute red team and purple team engagements simulating advanced threat actors across cloud infrastructure (AWS, Kubernetes), endpoints, and application surfaces Conduct continuous penetration testing of web applications, APIs, mobile clients, browser extensions, cloud infrastructure, and internal services Assess AI/ML-specific attack surfaces including prompt injection, model exfiltration, agent abuse, tool-use exploitation, and MCP security boundaries Develop and maintain custom offensive tooling, exploits, and automation to improve the efficiency and coverage of security testing Perform open-scope adversary simulations that test detection and response capabilities end to end, collaborating closely with the defensive security team Drive threat modeling sessions with engineering teams to identify and prioritize attack vectors in new features and architectures Deliver clear, actionable findings to both technical and executive audiences; partner with engineering to validate remediations Contribute to the security of CI/CD pipelines, supply chain integrity, and secrets management through offensive assessment Stay current on emerging attack techniques, vulnerability research, and adversary tradecraft; bring external perspective into Perplexity's security strategy Qualifications 5+ years of hands-on experience in offensive security, red teaming, or penetration testing Deep technical expertise in at least two of: clo

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

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

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

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

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

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 You'll build the backend systems that make Hark's AI agent actually work — reliable, fast, and production-grade. That means the hard infrastructure problems: high-concurrency services, low-latency streaming, state management for long-running agent workflows, and the execution layer that connects model outputs to real-world actions. You are building the nervous system of an agentic product. This is a high-ownership role on a small team. You'll work directly with model researchers and platform engineers, and the systems you build will determine whether Hark feels like a slow chatbot or something genuinely new. Responsibilities Core Runtime Architecture: Design and build the high-concurrency backend services responsible for agent orchestration, tool execution, and real-time streaming. Systems Reliability: Develop robust failure-handling, retry logic, and state management for long-running agentic workflows. Platform Primitives: Architect the foundational APIs and services—including memory retrieval systems and sandboxed execution environments—that power the entire Hark ecosystem. Performance Engineering: Optimize the stack for low-latency streaming and high-throughput data processing to ensure seamless agent-user interactions. Full-Cycle Owne

SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where we are not. Today, SpaceX is actively developing the technologies to make this possible, with the ultimate goal of making life multiplanetary and expanding consciousness to the stars. SpaceXSI is building Super Intelligence to help humanity understand the universe. Our teams are building the full Super Intelligence stack: from our Colossus supercomputers, to Grok models, to our suite of applications, including Grok Bot, Grok Build, Grok Imagine, Grok Voice, and X. We're creating a powerful flywheel where more compute trains better models, better models power more useful products, and what we learn from people using those products shapes what we build next. ABOUT THE ROLE: You will work on the most critical modeling challenges at any given time. You will get clarity on your first project before an offer. BASIC QUALIFICATIONS: You believe truth-seeking AI is the most important and challenging problem. You are obsessed about building incredibly useful models. You are a power user of AI models. If you previously trained models used by millions of people it’s a big plus, but modeling experience is not required. You take pride in your work and thrive in meritocratic environments. COMPENSATION AND BENEFITS: $180,000 - $600,000 USD Base salary is just one part of our total rewards package at SpaceXSI, which also includes equity, comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short & long-term disability insurance, life insurance, and various other discounts and perks. SpaceXSI is an equal opportunity employer. For details on data processing, view our Recruitment Privacy Notice .

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 You'll build the iOS experience for Hark: a native app that brings a real-time, multimodal AI agent into people's pockets. That means shipping an app that feels instant, handles streaming AI responses gracefully, and integrates voice, text, and vision into a single coherent experience. The bar is high: this is the primary way millions of people will interact with Hark. This is a high-ownership role on a small team. You'll work directly with designers, platform engineers, and the people building the models. What you ship will define how Hark feels in someone's hand. Responsibilities Build and own the Hark iOS app. Architecture, UI, performance, and the end-to-end experience. Ship features that integrate real-time AI capabilities: streaming responses, voice input, tool invocations, and multimodal interactions. Work closely with designers to craft interfaces that feel fast, polished, and trustworthy. Sweat the details. Optimize for performance at every layer: startup time, animation smoothness, memory efficiency, and network latency. Own components end-to-end, from design and implementation through testing, launch, and iteration. Collaborate with platform and backend engineers on APIs, data contracts, and integration with the agent runtime.