Вакансии

• Поэтапный перевод системы с графа сценариев и скиллов на управляемый LLM-based диалог. • Дебаг голосового пайплайна (поиск причин high latency, галлюцинаций LLM, проблем с передачей аудио, графовых ошибок и т.п.).

• Поэтапный перевод системы с графа сценариев и скиллов на управляемый LLM-based диалог. • Дебаг голосового пайплайна (поиск причин high latency, галлюцинаций LLM, проблем с передачей аудио, графовых ошибок и т.п.).

Location: Lugano, Switzerland Workplace: remote Join Tether and Shape the Future of Digital Finance At Tether, we’re not just building products, we’re pioneering a global financial revolution. Our cutting-edge solutions empower businesses—from exchanges and wallets to payment processors and ATMs—to seamlessly integrate reserve-backed tokens across blockchains. By harnessing the power of blockchain technology, Tether enables you to store, send, and receive digital tokens instantly, securely, and globally, all at a fraction of the cost. Transparency is the bedrock of everything we do, ensuring trust in every transaction. Innovate with Tether Tether Finance: Our innovative product suite features the world’s most trusted stablecoin, USDT , relied upon by hundreds of millions worldwide, alongside pioneering digital asset tokenization services. But that’s just the beginning: Tether Power: Driving sustainable growth, our energy solutions optimize excess power for Bitcoin mining using eco-friendly practices in state-of-the-art, geo-diverse facilities. Tether Data: Fueling breakthroughs in AI and peer-to-peer technology, we reduce infrastructure costs and enhance global communications with cutting-edge solutions like KEET , our flagship app that redefines secure and private data sharing. Tether Education : Democratizing access to top-tier digital learning, we empower individuals to thrive in the digital and gig economies, driving global growth and opportunity. Tether Evolution : At the intersection of technology and human potential, we are pushing the boundaries of what is possible, crafting a future where innovation and human capabilities merge in powerful, unprecedented ways. Why Join Us? Our team is a global talent powerhouse, working remotely from every corner of the world. If you’re passionate about making a mark in the fintech space, this is your opportunity to collaborate with some of the brightest minds, pushing boundaries and setting new standards. We’ve grown fast, stayed lean, and secured our place as a leader in the industry. If you have excellent English communication skills and are ready to contribute to the most innovative platform on the planet, Tether is the place for you. Are you ready to be part of the future? About the job As a member of our AI research team, you will drive innovation in model compression and efficient deployment for advanced multimodal AI systems, including large language models (LLMs) and vision-language models (VLMs). Your work will focus on reducing model footprint and computational cost while preserving accuracy, enabling high-performance AI to run efficiently across resource-constrained edge devices. You will apply and advance compression techniques such as quantization, knowledge distillation, and pruning to streamline complex multimodal architectures that integrate text, images, and audio. We expect you to have deep expertise in model compression methods and a strong background in multimodal model architectures. You will adopt a hands-on, research-driven approach to develop, test, and implement novel compression strategies that balance model size, latency, throughput, and accuracy. Your responsibilities include building robust compression pipelines, establishing performance and fidelity metrics, and addressing bottlenecks in production inference. The ultimate goal is to deliver scalable, low-memory, low-latency AI systems on edge devices (i.e., smartphones) that maintain high fidelity and tangible real-world value. Responsibilities Break down the key responsibilities in bullet points. It’s helpful to make them actionable and measurable. This could also be grouped into categories for more complex roles. Apply low-bit quantization to reduce model size and inference latency for generative AI models (LLMs, VLMs, multimodal) while maintaining accuracy and output quality. Leverage knowledge distillation to transfer capabilities from larger teacher models to smaller student models, enabling efficient multimodal reasoning across text, image, and audio inputs. Implement pruning techniques to remove redundant parameters and attention heads, reducing computational overhead without sacrificing task performance. Analyze trade-offs between model efficiency (size, latency, memory) and accuracy across quantization, distillation, and pruning methods; propose improvements based on empirical findings. Research and apply mixed-precision quantization and other advanced compression strategies (e.g., adaptive pruning schedules, distillation with intermediate feature matching) to optimize the accuracy–performance balance. Stay current with the latest research in model compression, including emerging techniques for multimodal and generative architectures. Document methodologies, experiments, and results clearly to support reproducibility, internal collaboration, and stakeholder communication. Author technical papers and publish findings in top-tier conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ACL, AAAI) to advance the field of model compression for multimodal AI. List the qualifications, certifications, and experience needed for the role. You can split this into mandatory and preferred sections if needed. A degree in Computer Science  or related field. Ideally PhD in NLP, Machine Learning, or a related field, complemented by a solid track record in AI R&D (with good publications in A* conferences). Experience with PyTorch deep learning frameworks or equivalent frameworks Hands-on experience with model quantization including both Quantization-Aware Training (QAT) and Post-Training Quantization (PTQ). Research and hands-on experience with knowledge distillation for compressing large models into smaller, efficient ones. Research and hands-on experience with model pruning for compressing large models into smaller, efficient ones. Solid understanding of neural network architectures and training processes – Including transformers (e.g., LLMs, VLMs), backpropagation, optimization, and fine-tuning techniques. Familiarity with C++ is a plus (especially for implementing low-level quantization kernels or inference optimizations). Important information for candidates Recruitment scams have become increasingly common. To protect yourself, please keep the following in mind when applying for roles: Apply only through our official channels. We do not use third-party platforms or agencies for recruitment unless clearly stated. All open roles are listed on our official careers page: https://tether.recruitee.com/ Verify the recruiter’s identity. All our recruiters have verified LinkedIn profiles. If you’re unsure, you can confirm their identity by checking their profile or contacting us through our website. Be cautious of unusual communication methods. We do not conduct interviews over WhatsApp, Telegram, or SMS. All communication is done through official company emails and platforms. Double-check email addresses. All communication from us will come from emails ending in @ tether.to or @ tether.io We will never request payment or financial details. If someone asks for personal financial information or payment at any point during the hiring process, it is a scam. Please report it immediately. When in doubt, feel free to reach out through our official website.

- Поэтапный перевод системы с графа сценариев и скиллов на управляемый LLM-based диалог; - Дебаг голосового пайплайна (поиск причин high latency, галлюцинаций LLM, проблем с передачей аудио, графовых ошибок и т.п.);

LLM/NLP: LLM/SLM, prompt engineering, few-shot, BERT, PEFT, LoRA/QLoRA. Voice AI: дообучение TTS, ASR (GigaAMv2), VAD, streaming ASR/TTS.

Location: Remote Workplace: Remote ABOUT US Launched in 2019, Constructor is an AI-first e-commerce search and discovery platform that helps shoppers find the right products at the right time and enables leading global e-commerce brands to drive meaningful revenue and conversion gains. ABOUT THE TEAM The SABR team owns the top layer of request processing for product discovery. We own the service that first receives product discovery requests (autocomplete, search, browse & recommendations) & executes the entire business logic that drives product discovery. That service also functions as a gateway to parse incoming user requests, orchestrate calls across the internal services that do the ranking and retrieval, interpret their responses, and assemble the final response the customer sees. We also own the public configuration APIs customers use to control how discovery behaves, and the MCP layer that exposes all of it to AI agents. Our team owns both platform & product components: Because of the positioning of our services, we take part in every architectural decision of our core product offering. At the same time, our goals are heavily influenced by direct customer feedback, because all product discovery-related features are either implemented in or integrated with our services. All of our services are public APIs, so interface design and backward compatibility are a constant part of the job. But most of our attention goes to keeping them fast and up: we serve up to 15k RPS, fan out to many internal services on every request, and are expected to stay available and degrade gracefully when any of them fails or slows down. The work is distributed systems in practice rather than in theory: request orchestration, failure isolation, caching, latency budgets, capacity planning, and the observability to know what is actually happening in production. The team is small enough that engineers own problems end to end, from design through on-call. ABOUT YOU You're a staff-level engineer who wants to own systems, not tickets. You've built high-traffic, low-latency Python services and carried the pager for them. You think in trade-offs: latency versus cost, flexibility versus a public API that customers can't afford to see break, the fix that ships this week versus the architecture that has to last two years. You can lead work that spans several engineers and several quarters, you enjoy mentoring others, and you're fine when a problem shows up half-defined. You don't mind being the one who reads the spec for some unfamiliar protocol, works out how it fits, and designs an integration that holds up at scale. You change your mind when someone has a better argument, you make the people around you better, and you still care about your code long after it merges. WHAT YOU WILL DO - Own the technical direction of one or more of our services - architecture, performance, and reliability. - Lead design of new systems and public APIs, and the evolution of existing ones as traffic and feature scope grow. - Raise the engineering bar through design and code review, and mentor mid and senior engineers into owning bigger scopes. - Partner with product, other engineering teams, and solutions/support to shape what we build and to represent search constraints and trade-offs honestly. - Take part in on-call for the systems you own, and lead incident response and follow-through when things break. WHAT WE ARE LOOKING FOR TECHNICAL - Substantial experience building and operating high-traffic, low-latency backend services in production. - Extensive Python knowledge (our primary language). - Experience with observability and performance work in live systems. - Experience designing and evolving public APIs that external customers depend on. - Experience designing & implementing scalable service-oriented architectures. BEYOND THE CODE - Track record of leading projects that span multiple engineers and quarters. - Influence without authority, and willingness to change your position when someone has a better argument. - Clear written communication - design docs, RFCs, postmortems. - Good judgment about trade-offs and scope. - Comfort with ambiguity and loosely defined problems. - Ownership that extends past merge, to how the system behaves in production. NICE TO HAVE - Experience with AWS - Background in search, ranking, information retrieval, or e-commerce product discovery. - Exposure to AI/LLM-facing infrastructure (MCP, agent tooling, or similar). BENEFITS 🏝️ Unlimited vacation time - we strongly encourage all of our employees take at least 3 weeks per year 🌎 Fully remote team - choose where you live 🛋️ Work from home stipend! We want you to have the resources you need to set up your home office 💻 Apple laptops provided for new employees 🧑‍🎓 Training and development budget for every employee, refreshed each year 👪 Maternity & Paternity leave for qualified employees 🧠 Work with smart people who will help you grow and make a meaningful impact 💵 Base salary: $110k–$130k USD, depending on knowledge, skills, experience, and interview results 📈 Stock options - offered in addition to the base salary 🎉 Regular team offsites to connect and collaborate DIVERSITY, EQUITY, AND INCLUSION AT CONSTRUCTOR At Constructor.io http://Constructor.io we are committed to cultivating a work environment that is diverse, equitable, and inclusive. As an equal opportunity employer, we welcome individuals of all backgrounds and provide equal opportunities to all applicants regardless of their education, diversity of opinion, race, color, religion, gender, gender expression, sexual orientation, national origin, genetics, disability, age, veteran status or affiliation in any other protected group. Studies have shown that women and people of color may be less likely to apply for jobs unless they meet every one of the qualifications listed. Our primary interest is in finding the best candidate for the job. We encourage you to apply even if you don’t meet all of our listed qualifications. How we handle your data. By submitting this application, you acknowledge that Constructor will collect and process the personal data you provide for the purpose of evaluating your candidacy for this role. If you are not selected, we will retain your data for a limited period as described in our Recruitment Privacy Notice. After that period your data will be deleted or anonymized. How we handle your data. By submitting this application, you acknowledge that Constructor will collect and process the personal data you provide for the purpose of evaluating your candidacy for this role. If you are not selected, we will retain your data for a limited period as described in our Recruitment Privacy Notice https://constructor.com/recruitment-privacy-notice. After that period your data will be deleted or anonymized.

Location: Stockholm 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 https://modal.com/blog/how-ramp-built-a-full-context-background-coding-agent-on-modal, 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 https://github.com/mwaskom/seaborn,Luigi https://github.com/spotify/luigi), 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 software that developers love to work with. Our ideal candidate is someone with a demonstrated drive to build beautiful abstractions that enhance developer productivity. WHAT YOU’LL WORK ON: - Improve the developer and agent experience of our SDK and CLI - Develop new primitives to meet demand for entirely new areas that arise as a result of the ongoing industry transformation YOU MAY BE A FIT IF: - You have 5+ years of experience developing high-quality Python, JavaScript, or Go applications or libraries where the code is used or interacted with by other developers - You have a strong code-as-product sense that manifests as a focus on developer ergonomics and productivity - You understand async programming, concurrency management, and their pitfalls - You have a high level of customer empathy, good communication skills, and an openness to working directly with our users to help solve their problems - You’re able to participate in our on-call rotation and respond to production incidents - You’re able to work in person in our Stockholm office NICE-TO-HAVE: - Experience building developer tools or SDKs - Experience maintaining open-source software - Good understanding of agentic development workflows - Familiarity with modern data, ML, and AI tools and workflows

Location: United Kingdom Remote; Canada Remote; Argentina Remote ABOUT THE TEAM The Canvas Core team builds and maintains the foundational platform that powers Mural’s visual thinking experience. This includes the infinite canvas, key editor components, document editing behaviors, asset management, real-time collaboration, and the systems that enable fast, reliable, and intuitive interaction on the canvas. We’re also responsible for the Mural UI, the real-time message protocol that enables seamless remote collaboration, and the developer-friendly APIs that internal teams use to build features like diagramming, workshops, presentations, integrations, and AI-enabled product capabilities. Our mission is to ensure the Mural editor is fast, reliable, intuitive, and easy to build on. We prioritize performance, simplicity, developer experience, and platform quality, enabling teams across the company to ship quickly and safely on top of Canvas Core. YOUR MISSION As a Senior Software Engineer, you’ll help design, build, and improve the Canvas platform so that the Mural editor remains reliable, high-performing, and intuitive for our users. You’ll work on the systems that power real-time collaboration, shared document editing, spatial interactions, rendering and interaction performance, asset management, developer APIs, and AI-enabled product capabilities across the Mural editor. Your role will be to reduce platform complexity, improve the quality and speed of Canvas development, and help teams ship high-quality editor experiences quickly and safely. You’ll partner closely with Product, Design, Engineering, and other stakeholders to turn ambiguous product and platform problems into clear, maintainable technical solutions. Senior Engineers at Mural lead by example through strong technical execution, thoughtful design, high-quality implementation, and collaborative problem-solving. They help raise the bar for their team through design discussions, code reviews, mentoring, documentation, and pragmatic improvements to engineering practices. WHAT YOU’LL DO - Own and deliver new Canvas platform capabilities and improvements from problem definition through implementation, release, measurement, and iteration - Partner with Product and Design to shape high-quality user experiences, balancing pragmatic technical delivery with long-term platform needs - Design and build maintainable Canvas platform systems, with accountability for quality, performance, reliability, and developer experience - Contribute to developer-friendly APIs, service boundaries, and platform contracts that internal teams can build on quickly and safely - Use AI-assisted tools and agentic workflows as part of your engineering practice to prototype, implement, test, document, and measure work effectively - Strengthen the team through technical design reviews, demos, code reviews, mentoring, and improvements to engineering practices - Build and evolve canvas systems with rich document and object models, including hierarchical scene or document structures, spatial indexing and querying, layout behavior, asset management, and selection mechanics - Work on large-scale concurrent and real-time collaboration systems that keep shared documents synchronized across users, contributing to design decisions around event ordering, latency, conflict handling, and failure-mode management - Help design, build, and integrate AI-enabled product capabilities where they intersect with the canvas, document model, real-time collaboration systems, or developer platform - Improve performance through profiling, bottleneck analysis, architectural simplification, targeted optimization, and moving expensive work out of critical interaction paths so systems remain responsive as document complexity and user activity scale WHAT YOU’LL BRING - Fluency in modern JavaScript/TypeScript, with familiarity in React, Node.js, or comparable modern frameworks - 6+ years building and shipping large-scale production software as part of an agile engineering team - Strong engineering judgment, with experience designing and delivering scalable, reliable, high-performance systems and developer-facing abstractions that balance simplicity, developer experience, and long-term maintainability - Experience designing clean API contracts and service boundaries, including thoughtful data models, versioning, validation, error handling, documentation, and long-term maintainability - Experience building distributed, concurrent, collaborative, or low-latency systems, such as collaboration tools, MMO games, shared-state systems, messaging protocols, or other low-latency user experiences, with familiarity across synchronization, consistency, event ordering, latency, failure modes, and performance trade-offs - Exposure to complex systems with rich object models, including hierarchical scene or document structures, spatial indexing and querying, layout behavior, asset management, selection mechanics, and performance-sensitive user interactions is a strong plus - Interest in AI-enabled product capabilities, or hands-on experience building or integrating them in production, such as intelligent editing, automation, recommendations, semantic document understanding, or collaboration features powered by AI - Performance optimization experience, including profiling, bottleneck analysis, memory and CPU efficiency, latency reduction, and responsiveness as document complexity and user activity scale - Familiarity with parallel processing, off-main-thread architectures, rendering pipelines, background computation, or other multithreaded systems is a plus - Practical experience using AI-assisted tools to prototype, implement, test, document, and measure engineering work - Communication and collaboration skills, with a low-ego approach to working with Product, Design, and Engineering, and the ability to contribute meaningfully to technical discussions, collaborate across teams, and help improve team engineering practices - Comfort operating in high-growth, fast-paced environments or scale-ups is a plus Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience. EQUAL OPPORTUNITY  We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

Location: New York Workplace: OnSite 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 https://modal.com/blog/how-ramp-built-a-full-context-background-coding-agent-on-modal, 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 https://github.com/mwaskom/seaborn,Luigi https://github.com/spotify/luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. 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 https://modal.com/blog/lovable-case-study, Ramp https://modal.com/blog/how-ramp-built-a-full-context-background-coding-agent-on-modal, 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 https://modal.com/blog/modal-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 https://github.com/mwaskom/seaborn,Luigi https://github.com/spotify/luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. THE ROLE: Modal builds the infrastructure that lets engineers run AI workloads without the usual pain. To do this well, we need exceptional people – and that’s where you come in. As the first dedicated technical recruiter on our Talent team, you’ll own engineering and AI/ML searches end-to-end. You’ll work closely with our Head of Talent, founders, and technical leads to shape how we hire and help bring in the people who will define what Modal becomes. What you’ll do: - Run full-cycle recruiting for engineering and AI/ML roles (sourcing, pitching, guiding interviews, and closing candidates) - Partner with technical leaders to understand the real work and calibrate on what great looks like - Help set our technical hiring bar and how we evaluate talent - Execute creative top-of-funnel strategies that resonate with a strong community of talented, experienced engineers - Deliver a fast, respectful, honest candidate experience - Bring an equity lens to every stage of the process - Use data and market context to keep searches on track and expectations aligned - Support candidates as a trusted guide through high-stakes decisions REQUIREMENTS: - You know technical recruiting inside and out and enjoy the challenge of deeply technical roles - You’re curious – you ask the right questions and love understanding how things actually work - You influence with insight and honesty, not by simply having the loudest voice in the room - You move quickly and communicate clearly, even when things get messy - You’re a strong closer who builds trust early and stays ahead of concerns - You’re steady when priorities shift and can recalibrate without losing momentum - You care about people and want them to have a thoughtful, fair, and human experience throughout the process

Location: San Francisco; New York Workplace: OnSite 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 https://modal.com/blog/how-ramp-built-a-full-context-background-coding-agent-on-modal, 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 https://github.com/mwaskom/seaborn,Luigi https://github.com/spotify/luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. THE ROLE: Modal builds the infrastructure that lets engineers run AI workloads without the usual pain. To do this well, we need exceptional people, and that’s where you come in. As the first dedicated GTM recruiter on our Talent team, you’ll own sales, GTM, and G&A searches end-to-end. You’ll work closely with our Head of Talent, founders, and GTM leads to shape how we hire and help bring in the people who will define what Modal becomes. WHAT YOU'LL WORK ON: - Drive full-cycle recruiting for key hires across GTM and G&A functions (sourcing, pitching, guiding interviews, and closing candidates) - Partner with GTM leaders to understand the real work and calibrate on what great looks like - Help set our hiring bar and how we evaluate talent - Execute creative top-of-funnel strategies that resonate with a strong community of experienced GTM talent - Deliver a fast, respectful, honest candidate experience - Bring an equity lens to every stage of the process - Use data and market context to keep searches on track and expectations aligned - Support candidates as a trusted guide through high-stakes decisions YOU MAY BE A FIT IF: - You know GTM recruiting inside and out and enjoy challenging searches - You’re curious: you ask the right questions and love understanding how things actually work - You influence with insight and honesty, not by simply having the loudest voice in the room - You move quickly and communicate clearly, even when things get messy - You’re a strong closer who builds trust early and stays ahead of concerns - You’re steady when priorities shift and can recalibrate without losing momentum - You care about people and want them to have a thoughtful, fair, and human experience throughout the process

Location: United States Who We Are MEMX is a technology-driven exchange operator founded by members to benefit all investors. We operate MEMX Equities, MEMX Options, and MX2 Options, and provide market technology to clients. Our mission is to create healthy competition and advocate for market structure reform that results in more efficient and sensible trading experiences for all investors. Description MEMX is seeking a Network Engineering Intern to learn how the networks behind our U.S. equities and options exchanges are built and supported. You’ll work alongside experienced engineers on hands-on projects and gain exposure to the reliable, low-latency infrastructure that supports trading. This internship position will be offered as hybrid with 1- day in person at our Data Center in North Bergen, NJ, and 2-days in person at our co-working office in Midtown -NYC . Work Schedule The intern will be expected to work the following schedule: Monday: 1:00pm – 10:00pm ET, in person at our North Bergen Data Center Tuesday: 10:00am – 6:00pm ET, remote Wednesday: 9:00am – 5:00pm ET, in person at our co-working office in Midtown-NYC Thursday: 9:00am – 5:00pm ET, in person at our co-working office in Midtown-NYC Friday: 9:00am – 5:00pm ET, remote Hours are subject to change based on operational needs. *MEMX has currently approved ONLY the following states for remote work: California, Colorado, Connecticut, Delaware, Florida, Georgia, Illinois, Kansas, Maine, Maryland, Massachusetts, Michigan, Nevada, New Jersey, New York, North Carolina, Pennsylvania, South Carolina, Texas, & Utah. What You’ll Be Doing Help the team monitor network performance and investigate alerts and connectivity issues Assist with network device configuration, testing, and documentation under the guidance of experienced engineers Assist with data center activities such as racking, network and hardware, running optical fibers, etc. Contribute to projects involving network tools, automation, and infrastructure improvements Collaborate with teams across MEMX to understand how network engineering supports the exchange Requirements Current undergraduate student entering their junior or senior year, pursuing Computer Science, Information Technology, Network Engineering, or a related field Foundational understanding of networking concepts such as IP addressing, routing, and switching through coursework, projects, or personal interests Interest in troubleshooting and learning how large-scale networks operate Strong attention to detail and willingness to ask questions and learn from the team Exposure to Python, Linux, or Wireshark is a plus, but not required Ability to work in person at our Midtown Manhattan office during the summer Permanent residence in one of MEMX’s approved states for remote work during the internship What You’ll Gain Hands-on experience with the network infrastructure that supports a securities exchange Exposure to various Options and Equities exchange platforms and how network connectivity supplements these platforms Exposure to network monitoring, troubleshooting, and day-to-day operations Learn how customer connections are set up and supported Mentorship and guidance from experienced network engineers Opportunities to collaborate with technology teams across MEMX and connect with fellow interns Why MEMX At MEMX, you’ll contribute to meaningful work alongside experienced professionals while developing your skills and learning how our exchanges operate. As part of our summer internship program, you’ll also have access to: Learning opportunities: Attend Lunch & Learn sessions, professional development workshops, and relevant courses Mentorship and support: Learn from a mentor and a designated buddy who can help guide you throughout the summer An intern cohort: Connect with interns working across other MEMX teams Social events: Get to know colleagues, with opportunities to connect with members of MEMX’s C-suite Regular feedback: Check in with your manager and HR to discuss your progress, ask questions, and get support Future opportunities: All interns are considered for potential internship extensions or a full-time opportunity after graduation, based on performance and business needs Pay Rate: $30/hourly for undergraduate students Equal Opportunity Statement MEMX is an equal opportunity employer. We are committed to creating a diverse and inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. Diversity Inclusion Statement At MEMX, we believe that diversity and inclusion are essential to driving innovation and success. We welcome and celebrate individuals from all backgrounds and perspectives, and we strive to create an inclusive culture where everyone can thrive.

Location: Poland; Brazil; Peru; Sweden; Colombia; Argentina; Romania; Slovenia; Lithuania; South Africa; Czech Republic; Hungary; Mexico; Chile; Slovakia; Bulgaria Workplace: Remote BUILDING THE FUTURE OF OPEN FINANCE Payward - the parent company behind Kraken, NinjaTrader, Breakout, xStocks, Payward Services and CF Benchmarks - has spent the last 15 years building one of the most modern and globally accessible financial infrastructure platforms in the industry, built to advance an open, global financial system. THE TEAM   Payward Services is an enterprise infrastructure platform that enables companies to seamlessly integrate trading, payments, funding, and digital asset services through a single unified system. It provides coordinated liquidity, custody, compliance, risk management, and settlement capabilities, reducing operational complexity for fintechs, banks, brokerages, and payment providers. As a Software Engineer in Payward Services you'll build and scale the systems that make this platform work under the hood, from real-time coordination across services to the infrastructure enterprise partners depend on to move money and assets safely, at scale, every day. We’re looking for builders who thrive in ambiguity, move quickly with ownership, and care deeply about creating robust solutions.   THE OPPORTUNITY - Design and implement robust Rust services and libraries that power trading, payments, and crypto experiences with a focus on reliability, performance, and user impact. - Write reusable, testable, and highly efficient code that scales across teams and supports revenue-critical systems without compromising safety or security. - Collaborate on large-scale distributed systems architecture, translating evolving product requirements into resilient, low-latency solutions. - Work alongside hundreds of experienced Rust engineers, contributing to a high-performance, product-driven engineering culture.   WHAT YOU BRING - 3+ years of software engineering experience - Proficient in writing network services or asynchronous code in Rust - Have a security-first mindset during system design to ensure robustness - Demonstrate the ability to autonomously debug issues across the stack (OS, network, application) - Apply a solid understanding of distributed systems and technologies, including RPC protocols, Kafka, and Event-Driven Systems, to design scalable solutions - Collaborate effectively with product teams to gather requirements and constraints for designing appropriate systems - Take complete end-to-end ownership of systems and libraries   NICE TO HAVES - Experience building B2B focused products, ideally in the fintech or crypto space Unless a specific application deadline is stated in the job posting, applications are accepted on an ongoing basis. Please note, applicants are permitted to redact or remove information on their resume that identifies age, date of birth, or dates of attendance at or graduation from an educational institution. We consider qualified applicants with criminal histories for employment on our team, assessing candidates in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance. OUR COMMITMENT Payward is powered by people from around the world and we celebrate the diverse talents, backgrounds, contributions, and unique perspectives that everyone brings to the table. We hire based on merit, seeking out people with the right abilities, knowledge, and skills for the job. We encourage you to apply for roles where you don't fully meet the listed requirements, especially if you're passionate or knowledgeable about crypto. We may ask candidates to complete job-related skills or work-style assessments as part of our hiring process. These assessments evaluate competencies relevant to the role and are applied consistently across candidates for similar positions. Results are considered alongside experience and interviews, and are not the sole basis for any employment decision. As an equal opportunity employer, we don't tolerate discrimination or harassment of any kind, whether based on race, ethnicity, age, gender identity, citizenship, religion, sexual orientation, disability, pregnancy, veteran status, or any other protected characteristic as outlined by federal, state, or local laws. Stay connected Follow us on Twitter https://twitter.com/krakenfx Learn on the Kraken Blog https://blog.kraken.com/#:~:text=Enter%20your%20email%20address Connect on LinkedIn https://www.linkedin.com/company/kraken-exchange/ Candidate Privacy Notice https://www.kraken.com/legal/candidate-privacy-notice

Задачи: — Повышение эффективности утилизации GPU: формирование гипотез, исследование способов повышения эффективности, участие в реализации и внедрении решений. — Формирование рекомендаций и лучших практик по повышению производительности GPU-инфраструктуры. — Оптимизация и профилирование: поиск узких мест в производительности и их устранение с помощью профилировщиков, оптимизация доступа к памяти, ядрам, времени ожидания и пропускной способности. — Развитие инструментов диагностики: создание и улучшение инструментов для выявления и устранения инфраструктурных проблем, влияющих на эффективность утилизации, стабильность и скорость GPU-вычислений для обучения и инференса. — Исследование и внедрение современных решений: изучение новейших подходов к организации инфраструктуры для обучения и инференса, оценка их эффективности и внедрение в проекты. — Анализ архитектуры, тестирование, интеграция: взаимодействие с разработчиками, ML-инженерами и системными архитекторами, участие в оценке аппаратных решений, предложение улучшений для будущих поколений GPU, разработка планов тестирования, формирование бенчмарков, анализ регрессий производительности. Требования: — Знание Python и опыт системного программирования, разработка библиотек или фреймворков. — Опыт работы с PyTorch и распределённым обучением через torch.distributed. — Применение подходов параллелизации (data parallelism, tensor parallelism, pipeline parallelism, expert parallelism) для распределённого инференса или обучения. — Интерес к LLM и MLOps, понимание задач и вызовов эксплуатации больших моделей в продакшене. — Опыт работы с GPU (NVIDIA) и CUDA: понимание архитектуры GPU, разработка или оптимизация алгоритмов под CUDA, использование Nsight, nvprof или аналогов. — Умение оптимизировать производительность GPU-приложений и повышать эффективность утилизации GPU. — Способность анализировать профили и метрики производительности. — Навыки чтения и оптимизации сложного кода. — Эффективная командная работа и готовность делиться знаниями. Будет плюсом: — Уверенное владение C/C++ или аналогичными низкоуровневыми языками. — Опыт работы с библиотеками RL-обучения для LLM: veRL, slime, NeMo-RL, SkyRL и другими. — Опыт работы с библиотеками инференса: vLLM, SGLang, TRTLLM. — Опыт оптимизации под реальные продакшен-нагрузки, работа с low-latency- или real-time-системами.

Location: Europe; London; Munich; Zurich Workplace: Remote Synthesia is the world’s leading AI video platform for business, used by over 90% of the Fortune 100. Founded in 2017, the company is headquartered in London, with offices and teams across Europe and the US. As AI continues to shape the way we live and work, Synthesia develops products to enhance visual communication and enterprise skill development, helping people work better and stay at the center of successful organizations. Following our recent Series E funding round, where we raised $200 million, our valuation stands at $4 billion. Our total funding exceeds $530 million from premier investors including Accel, NVentures (Nvidia's VC arm), Kleiner Perkins, GV, and Evantic Capital, alongside the founders and operators of Stripe, Datadog, Miro, and Webflow. ABOUT THE ROLE As a Staff Research Scientist, you will join a team of 40+ researchers and engineers in our R&D department, working on the frontier of generative AI with a focus on avatar-centric, interactive video diffusion models. This is a unique opportunity for experts in machine learning and diffusion models to shape the future of AI video agents that listen, respond, and react like humans. As part of our Interactive Avatars team, you'll build models that hold natural, real-time conversations: understanding what a user says and how they say it, then responding with appropriate turn-taking, backchannels, gaze, and facial and body reactions. You'll join a team that moves fast, iterates often, and turns breakthrough research into product capabilities that ship. WHAT YOU'LL DO - Set the research direction and roadmap for dyadic interaction modeling, balancing long-term bets with near-term product impact. - Advance the state of the art in the perceptual layer of interactive agents, including understanding user audio and video and generating contextually appropriate reactions. - Post-train multimodal models to generate rich, natural dyadic interactions from user audio and video inputs. - Adapt diffusion models to new conditioning signals, such as conversational state, turn-taking, and listener cues. - Build robust evaluation frameworks and test suites for continuous tracking of interaction quality. - Partner with our data team to define data needs and shape high-quality datasets. - Lead and mentor a small group of researchers, and drive technical decisions across research, data, and engineering. WHAT WE'RE LOOKING FOR: - Deep ML expertise and extensive hands-on experience with diffusion models, ideally for video or avatar generation. - A strong publication record at top-tier venues (e.g., CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR, SIGGRAPH) in areas such as world models, dyadic interaction, or video diffusion, or equivalent demonstrated impact. - Experience leading a small team of researchers and mentoring junior members. - A track record of taking research from idea to production. - Proficiency in PyTorch and modern ML tooling for large-scale training. - Clear communication of hypotheses, experiments, and results, and the ability to influence direction across teams. NICE TO HAVE - Experience with real-time or streaming generation, including autoregressive video diffusion. - Distillation or other techniques for low-latency inference. - Audio-driven facial, gesture, or full-body motion modeling. - Conversational modeling, such as turn-taking, backchanneling, or listener-response generation. Why join us? We’re living the golden age of AI. The next decade will yield the next iconic companies, and we dare to say we have what it takes to become one. Here’s why, OUR CULTURE At Synthesia we’re passionate about building, not talking, planning or politicising. We strive to hire the smartest, kindest and most unrelenting people and let them do their best work without distractions. Our work principles serve as our charter for how we make decisions, give feedback and structure our work to empower everyone to go as fast as possible. You can find out more about these principles here. https://www.notion.so/How-we-work-at-Synthesia-f794caa72f8446efb6be22b551ce0fa2?pvs=21 SERVING 50,000+ CUSTOMERS (AND 50% OF THE FORTUNE 500) We’re trusted by leading brands such as Heineken, Zoom, Xerox, McDonald’s and more. Read stories from happy customers https://www.synthesia.io/case-studies and what 1,200+ people say on G2 https://www.g2.com/products/synthesia/reviews#reviews. PROPRIETARY AI TECHNOLOGY Since 2017, we’ve been pioneering advancements in Generative AI. Our AI technology is built in-house, by a team of world-class AI researchers and engineers. Learn more about our AI Research Lab and the team behind. https://www.synthesia.io/research AI SAFETY, ETHICS AND SECURITY AI safety, ethics, and security are fundamental to our mission. While the full scope of Artificial Intelligence's impact on our society is still unfolding, our position is clear: People first. Always.  Learn more about our commitments to AI Ethics, Safety & Security https://www.synthesia.io/ethics. THE GOOD STUFF... - Competitive compensation - Hybrid work setting with an office in London, Zurich, Munich, or remote in Europe.  - 25 days of annual leave + public holidays - Great company culture with the option to join regular planning and socials at our hubs - + other benefits depending on your location You can see more about Who we are and How we work here: https://www.synthesia.io/careers https://www.synthesia.io/careers

Специалист будет отвечать за проектирование и развитие торговой инфраструктуры: управление жизненным циклом ордеров, маршрутизацию, интеграции с биржами и брокерами, pre-trade контроль рисков. Роль предполагает техническое лидерство в направлении: принятие архитектурных решений, ревью кода и работу с командой разработки.

Location: Hong Kong, Hong Kong SAR; Singapore, Singapore Who We Are At OKX, we believe that the future will be reshaped by crypto, and ultimately contribute to every individual's freedom. OKX is a leading crypto exchange, and the developer of OKX Wallet, giving millions access to crypto trading and decentralized crypto applications (dApps). OKX is also a trusted brand by hundreds of large institutions seeking access to crypto markets. We are safe and reliable, backed by our Proof of Reserves. Across our multiple offices globally, we are united by our core principles: We Before Me , Do the Right Thing , and Get Things Done . These shared values drive our culture, shape our processes, and foster a friendly, rewarding, and diverse environment for every OK-er. OKX is part of OKG, a group that brings the value of Blockchain to users around the world, through our leading products OKX, OKX Wallet, OKLink and more. About the Opportunity We are looking for an experienced blockchain developer to join our team building the next generation of high-performance on-chain trading infrastructure. You will help design and implement a unified trading engine — supporting Perpetuals, Spot, and Prediction Markets under a single margin account — and contribute to ExchangeOS , an infrastructure layer that lets KYC'd institutions and Web3 entities stake to create and operate their own trading venues (DEXs) on top of our chain. What You’ll Be Doing Design and build a unified account and matching system that supports Perpetuals, Spot, and Prediction Markets — including on-chain order matching, cross-margin validation, settlement, and liquidation/risk engines (ADL, ADL-avoidance, ADL waterfall, ecosystem insurance fund mechanics). Build and optimize the core components of ExchangeOS : the staking/venue-creation framework that allows KYC-verified institutions and Web3 protocols to launch and operate their own dex on shared infrastructure. Drive performance engineering across the stack — parallel transaction execution, low-latency order pipelines, and throughput/latency optimization at the engine and chain level. Track cutting-edge blockchain and trading-system technology (e.g. Hyperliquid, dYdX, other high-performance perp DEX architectures) and apply best practices to our infrastructure. Partner with product and business teams to translate venue/exchange requirements into technical designs, and provide ongoing technical support. What We Look For In You Strong proficiency in Rust , with hands-on experience in high-performance, low-latency systems; experience with parallel/concurrent execution engines is a strong plus. Deep understanding of exchange/matching engine mechanics: order book design, margin systems, liquidation and ADL, settlement, and risk engines — familiarity with perpetual, spot, or prediction market products is a strong plus. Solid grounding in blockchain fundamentals (consensus, P2P networking, cryptography); experience reading core code of major L1/L2 systems (Ethereum, Optimism, Arbitrum, or high-performance L1s like Hyperliquid/Solana) is a plus but not the primary focus of this role. Strong systems-performance mindset: profiling, memory/allocator tuning, and designing for sub-millisecond latency at scale. Excellent teamwork, communication, and logical reasoning skills; genuine passion for trading systems and blockchain technology. Perks & Benefits Competitive total compensation package L&D programs and Education subsidy for employees' growth and development Various team building programs and company events Wellness and meal allowances Comprehensive healthcare schemes for employees and dependants More that we love to tell you along the process! Notice: All official OKX vacancies are published on this website. While roles may appear on selected third-party platforms from time to time, information on other sites may be inaccurate or outdated. If in doubt, please apply directly through our official careers website. Information collected and processed as part of the recruitment process of any job application you choose to submit is subject to OKX 's Candidate Privacy Notice .

Location: San Francisco; Toronto; New York; Montreal; Seattle Workplace: Hybrid ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F https://www.baseten.co/blog/announcing-our-series-f/, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE We're looking for distributed systems engineers and product-minded generalists to build the distributed runtime that powers large-scale LLM inference on Baseten. Our inference platform empowers customers to deploy and operate cutting-edge models with industry-leading performance, scalability, and reliability. It also powers Model APIs, our hosted endpoints for the latest open-source models. You'll work across the stack, from the developer experience customers use to deploy models, through the libraries behind features like tool calling and reasoning, down to the systems that orchestrate deployments on Kubernetes and route traffic efficiently. Your job is to make sure every model on our platform is fast, reliable, and cost-efficient. You'll join a small, high-impact team at the intersection of distributed systems, model performance, infrastructure, and product, helping define how developers use AI models at scale. This role is ideal for engineers who enjoy owning systems in production, solving hard integration problems, and making complex infrastructure simple and reliable for users.   EXAMPLE INITIATIVES You'll get to work on these types of projects on our Inference Platform: - The Baseten Inference Stack at NVIDIA Dynamo Day https://www.baseten.co/blog/nvidia-dynamo-day-baseten-inference-stack/ - 2x faster inference with KV cache-aware routing https://www.baseten.co/blog/how-baseten-achieved-2x-faster-inference-with-nvidia-dynamo/ - How Baseten multi-cloud capacity management (MCM) unifies deployments https://www.baseten.co/blog/how-baseten-multi-cloud-capacity-management-mcm-powers-cloud-self-hosted-and-hybr/#comparing-deployment-options-cloud-vs-self-hosted-vs-hybrid RESPONSIBILITIES - Build the infrastructure and orchestration systems that deploy and run large-scale distributed LLM inference, including routing, autoscaling, scheduling, and runtime management. - Design, build, and operate Model APIs, with a focus on advanced inference capabilities: structured outputs (JSON mode, grammar-constrained generation), tool/function calling, and multimodal serving. - Implement platform fundamentals such as API versioning, validation, usage metering, quotas, and authentication. - Instrument deep observability (metrics, traces, logs) and build repeatable benchmarks for speed, reliability, and quality. Help set best practices for testing, release automation, and operational excellence. - Debug and harden complex production systems spanning Kubernetes, distributed runtimes, networking, and GPU workloads to improve reliability and scalability. - Partner with Inference Performance engineers and other teams to make new optimizations broadly available to customers and easy to configure. - Own projects end to end, from architecture through deployment, monitoring, and iteration on customer feedback. Along the way, make thoughtful tradeoffs between performance, reliability, operational simplicity, and developer experience.   REQUIREMENTS - Bachelor's, Master's, or Ph.D. in Computer Science, Engineering, or a related field, or equivalent practical experience. - 3+ years building and operating distributed systems, backend infrastructure, or large-scale APIs where reliability, latency, and scale are first-class concerns. - A proven track record of owning low-latency, reliable backend services, including rate limiting, auth, quotas, metering, and migrations. - Infrastructure instincts with a feel for performance: profiling, tracing, capacity planning, and SLO management. - Comfort debugging performance and reliability issues across multiple layers of the stack, from application behavior down to runtime and infrastructure internals. - A strong sense of developer experience. You think about how systems are used, not just how they work. - Eagerness to learn new languages, frameworks, and systems, and a real interest in inference engineering. Prior ML or LLM experience isn't required, though experience with model serving or inference systems is a plus. - Excellent written communication and collaboration skills, including writing clear design docs and working across functions.   NICE TO HAVE - Experience with or contributions to LLM inference engines and frameworks such as vLLM, SGLang, TensorRT-LLM, TGI, or Dynamo. - Deep Kubernetes experience, including operators and custom resources, plus familiarity with service meshes or API gateways. - Experience with distributed scheduling, autoscaling, or service orchestration. - Experience operating GPU workloads in production. - A background in developer-facing infrastructure or APIs, or contributions to open-source infrastructure or ML systems. - Familiarity with observability tooling, CI/CD systems, or release automation. BENEFITS - Competitive compensation, including meaningful equity - (U.S. only) 100% coverage of medical, dental, and vision insurance for employee and dependents - Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!) - Paid parental leave - Fertility and family-building stipend through Carrot - (U.S. only) Company-facilitated 401(k) - Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities. Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you. At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).

Location: San Francisco Workplace: OnSite 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 https://modal.com/blog/how-ramp-built-a-full-context-background-coding-agent-on-modal, 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 https://github.com/mwaskom/seaborn,Luigi https://github.com/spotify/luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. THE ROLE: Modal’s Inference Runtime team owns the container runtime stack used to run inference and training workloads across our fleet. We work at the boundary of Linux, containers, filesystems, storage, GPU drivers, and distributed systems. Our goal is to make demanding ML workloads start quickly, run efficiently, and remain securely isolated, whether they use a single GPU, hundreds of gigabytes of memory, or multiple GPUs connected with RDMA. We’re looking for a systems engineer who enjoys working deep in the stack. You’ll build production runtime infrastructure in Rust and Go, diagnose difficult Linux and performance problems, and help determine the architecture of Modal’s container platform. You’ll also work closely with maintainers of gVisor and contribute to the runtime itself when the right fix belongs upstream. WHAT YOU'LL WORK ON: - Make container startup, checkpoint, and restore dramatically faster for large inference and training workloads - Build multi-GPU and accelerator-aware snapshotting, including efficient handling of GPU memory and RDMA-enabled workloads - Design zero-copy and low-copy data paths between container memory, filesystems, storage, and Modal’s runtime - Optimize large snapshot pipelines using techniques such as parallel uploads, direct I/O, incremental snapshots, and more efficient memory handling - Improve container image and filesystem performance across EROFS, FUSE, page caches, overlay filesystems, and remote storage - Extend our sandboxed runtime to support new GPUs, drivers, profiling tools, and device capabilities across NVIDIA and AMD hardware - Debug complex failures involving system calls, virtual memory, process lifecycle, kernel behavior, GPU drivers, and container isolation - Safely roll out runtime and kernel changes across a heterogeneous fleet using compatibility controls, scheduling constraints, feature flags, and observability - Work across the runtime, scheduler, storage, and GPU infrastructure, and take ambiguous production problems from investigation through deployment YOU MAY BE A FIT IF: - You have strong Linux systems knowledge, particularly processes, virtual memory, filesystems, system calls, scheduling, namespaces, cgroups, and signals - You’ve built or debugged container runtimes, sandboxes, the Linux kernel, or similarly low-level infrastructure - You have strong programming ability in Rust, Go, or another systems language, and an interest in becoming productive in both Rust and Go - You’ve profiled and improved systems where memory movement, I/O, synchronization, or kernel interactions dominate performance - You’re comfortable debugging across abstraction boundaries, from application behavior down through runtimes, drivers, and the kernel - You can turn loosely defined production problems into well-designed, reliable systems - You want to own important infrastructure and work closely with both internal teams and customers NICE-TO-HAVE: Any of the following would be helpful, but none is required: - gVisor, runsc, runc, OCI runtimes, seccomp, or checkpoint/restore systems - Linux kernel development, virtualization, sandboxing, kernel modules, or device proxying - CUDA, ROCm, GPU drivers, accelerator virtualization, or GPU profiling - RDMA and high-performance networking - FUSE, EROFS, direct I/O, mmap, page-cache behavior, or storage engines - Large-memory or multi-GPU inference and training systems - Contributions to open-source systems software Prior gVisor or machine-learning experience is not required. We care more about strong systems fundamentals, curiosity, and the ability to learn unfamiliar parts of the stack. WHY THIS ROLE: The container runtime is directly on the critical path for inference performance. Improvements here can substantially reduce cold starts, increase token throughput, unlock new accelerator types, and make previously impractical workloads possible. This is an opportunity to work on unusually deep systems problems with immediate production impact. You’ll have room to shape the architecture, contribute to open-source runtime technology, and take ownership of foundational infrastructure used by every inference and training workload on Modal.