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Location: Tiranë, Albania; Andorra la Vella, Andorra; Buenos Aires, Argentina; Yerevan, Armenia; Brussels, Belgium; Sao Paulo, Brazil; Budapest, Hungary; Sofia, Bulgaria; Bogotá, Colombia; Zagreb, Croatia; Prague, Czechia; Copenhagen, Denmark; Cairo, Egypt; Tbilisi, Georgia; Athens, Greece; Bangalore, India; Dublin, Ireland; Rome, Italy; Luxemburg, Luxembourg; Sliema, Malta; Podgorica, Montenegro; Lagos, Nigeria; Oslo, Norway; Islamabad, Pakistan; Warsaw, Poland; Lisbon, Portugal; Bucharest, Romania; Belgrade, Serbia; Barcelona, Spain; Stockholm, Sweden; Berne, Switzerland; Dodoma, Tanzania, United Republic of; Abu Dhabi, United Arab Emirates; London, United Kingdom 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 Our pioneering P2P development platform, built on our open-source technology stack, Pear, eliminates the need for traditional server infrastructure. Pear platform facilitates direct deployment of applications from the developer’s machine to the user, enabling seamless scalability and performance. By leveraging Node.js-based technology akin to BitTorrent, we create robust peer-to-peer connections and data replication systems that set the foundation for a decentralized web. Learn more about Pear: docs.pears.com Keet, our flagship P2P communications app, is the first step towards this new era. It exemplifies the potential of P2P technology in everyday applications, from messaging and file sharing to complex collaborative environments, all while maintaining user sovereignty over personal data. Learn more about Keet: keet.io Responsibilities In this role, you will be responsible for developing and maintaining Keet Desktop, our cross-platform P2P communications application built with React and running on the Pear runtime. You'll work on everything from UI/UX implementation to performance optimization, helping shape the future of decentralized communication. Proven experience with React/Preact and modern JavaScript/TypeScript in production-scale applications. Strong competency in state management (Redux, Redux Toolkit, Zustand, or similar). Ability to write modular, maintainable, and well tested code. Solid skillset in testing & debugging complex frontend applications. Deep interest or experience with P2P technologies or distributed systems. Comfort working in a remote, globally distributed team; good communication skills. Preferred Qualifications Experience with desktop application development (Electron, Tauri, or similar runtimes). Familiarity with video/audio APIs (WebRTC, media streams) and real-time communication. Demonstrated ability to optimize UI performance: rendering, memory management. Experience building cross platform applications (macOS, Windows, Linux, etc). Bonus: Past contributions to OSS projects, especially in P2P or decentralized tech. 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.

Location: Berlin, Germany About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. The role Nebius Token Factory is looking for scientists who can turn frontier LLM and VLM inference bottlenecks into research questions, conduct rigorous experiments, and translate their findings into production capabilities. You will own focused research and optimization projects, write strong code, and produce prototypes, publications, and technical artifacts that engineers can build on. Your research will span quantization, distillation, speculative decoding, KV-cache optimization, and model/runtime co-optimization, alongside inference engines and distributed inference architectures. You will investigate how these approaches interact, evaluate their trade-offs across model quality, latency, throughput, memory footprint, and cost per token, and work with engineering teams to bring promising results into production. Your responsibilities Lead research projects in efficient LLM and VLM inference, from hypotheses and experiments through ablations, prototypes, and production handoff. Develop and evaluate methods spanning quantization, quantization-aware training (QAT), distillation, speculative decoding, KV-cache reuse, KV-cache compression, long-context inference, MoE routing, and model/runtime co-optimization. Build prototypes using PyTorch, Triton, CUDA-adjacent tooling, or inference-serving frameworks, and collaborate with MLEs and platform engineers to turn them into production components. Research LLM request routing and scheduling strategies, including cache-aware load balancing and prefill–decode disaggregation (PDD). Evaluate how queueing, KV-cache transfer, worker placement, and prefill/decode capacity allocation affect latency, throughput, and serving cost. Investigate multi-node inference for dense and mixture-of-experts models, including wide expert parallelism (WideEP). Study expert placement, load imbalance, and computation/communication trade-offs, and use the findings to guide model and system architecture choices. Develop rigorous evaluations covering quality, latency, throughput, numerical stability, memory footprint, tail latency, and cost per token. Compare serving architectures under consistent workload conditions and GPU budgets. Work with MLE, GPU kernel, backend infrastructure, product, and customer teams to select research priorities with measurable production impact. Share results through internal reports, technical blogs, papers, and open-source artifacts, and mentor engineers and scientists on experimental design, scientific rigor, and model/system trade-offs. Must-haves A PhD in computer science, machine learning, ML systems, computer systems, computer architecture, electrical engineering, applied mathematics, or a closely related discipline. A strong publication record or equivalent research artifacts in ML, ML systems, efficient inference, model compression, quantization, distillation, serving systems, or related areas. Strong Python and PyTorch implementation skills, with the ability to turn ideas into experiments and working prototypes. Deep knowledge of LLMs, VLMs, transformer inference, decoding algorithms, model compression, quantization, and production-serving trade-offs. Strong experimental design skills covering ablations, baselines, metrics, statistical reasoning, and failure analysis. Excellent written and verbal communication. Nice-to-haves First-author publications at venues such as NeurIPS, ICML, ICLR, MLSys, ACL, EMNLP, ASPLOS, OSDI, SOSP, ISCA, or HPCA. Experience deploying ML models or inference optimizations in production. Experience with vLLM, SGLang, TensorRT-LLM, NVIDIA Dynamo, FlashAttention, FlashInfer, Triton, CUDA, or PyTorch internals. Experience applying post-training, SFT, DPO, RLHF, RLAIF, preference optimization, or synthetic data generation to inference quality or efficiency. Open-source research artifacts, widely used benchmarks, technical blogs, or invited talks demonstrating contributions to efficient AI systems. Research or implementation experience in one or more areas of distributed inference system architecture, such as LLM request routing, PDD, multi-node serving, or MoE expert parallelism, including WideEP. Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

Location: Zurich, Switzerland About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. The role Nebius Token Factory is looking for scientists who can turn frontier LLM and VLM inference bottlenecks into research questions, conduct rigorous experiments, and translate their findings into production capabilities. You will own focused research and optimization projects, write strong code, and produce prototypes, publications, and technical artifacts that engineers can build on. Your research will span quantization, distillation, speculative decoding, KV-cache optimization, and model/runtime co-optimization, alongside inference engines and distributed inference architectures. You will investigate how these approaches interact, evaluate their trade-offs across model quality, latency, throughput, memory footprint, and cost per token, and work with engineering teams to bring promising results into production. Your responsibilities Lead research projects in efficient LLM and VLM inference, from hypotheses and experiments through ablations, prototypes, and production handoff. Develop and evaluate methods spanning quantization, quantization-aware training (QAT), distillation, speculative decoding, KV-cache reuse, KV-cache compression, long-context inference, MoE routing, and model/runtime co-optimization. Build prototypes using PyTorch, Triton, CUDA-adjacent tooling, or inference-serving frameworks, and collaborate with MLEs and platform engineers to turn them into production components. Research LLM request routing and scheduling strategies, including cache-aware load balancing and prefill–decode disaggregation (PDD). Evaluate how queueing, KV-cache transfer, worker placement, and prefill/decode capacity allocation affect latency, throughput, and serving cost. Investigate multi-node inference for dense and mixture-of-experts models, including wide expert parallelism (WideEP). Study expert placement, load imbalance, and computation/communication trade-offs, and use the findings to guide model and system architecture choices. Develop rigorous evaluations covering quality, latency, throughput, numerical stability, memory footprint, tail latency, and cost per token. Compare serving architectures under consistent workload conditions and GPU budgets. Work with MLE, GPU kernel, backend infrastructure, product, and customer teams to select research priorities with measurable production impact. Share results through internal reports, technical blogs, papers, and open-source artifacts, and mentor engineers and scientists on experimental design, scientific rigor, and model/system trade-offs. Must-haves A PhD in computer science, machine learning, ML systems, computer systems, computer architecture, electrical engineering, applied mathematics, or a closely related discipline. A strong publication record or equivalent research artifacts in ML, ML systems, efficient inference, model compression, quantization, distillation, serving systems, or related areas. Strong Python and PyTorch implementation skills, with the ability to turn ideas into experiments and working prototypes. Deep knowledge of LLMs, VLMs, transformer inference, decoding algorithms, model compression, quantization, and production-serving trade-offs. Strong experimental design skills covering ablations, baselines, metrics, statistical reasoning, and failure analysis. Excellent written and verbal communication. Nice-to-haves First-author publications at venues such as NeurIPS, ICML, ICLR, MLSys, ACL, EMNLP, ASPLOS, OSDI, SOSP, ISCA, or HPCA. Experience deploying ML models or inference optimizations in production. Experience with vLLM, SGLang, TensorRT-LLM, NVIDIA Dynamo, FlashAttention, FlashInfer, Triton, CUDA, or PyTorch internals. Experience applying post-training, SFT, DPO, RLHF, RLAIF, preference optimization, or synthetic data generation to inference quality or efficiency. Open-source research artifacts, widely used benchmarks, technical blogs, or invited talks demonstrating contributions to efficient AI systems. Research or implementation experience in one or more areas of distributed inference system architecture, such as LLM request routing, PDD, multi-node serving, or MoE expert parallelism, including WideEP. Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

Location: London, United Kingdom About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. The role Nebius Token Factory is looking for scientists who can turn frontier LLM and VLM inference bottlenecks into research questions, conduct rigorous experiments, and translate their findings into production capabilities. You will own focused research and optimization projects, write strong code, and produce prototypes, publications, and technical artifacts that engineers can build on. Your research will span quantization, distillation, speculative decoding, KV-cache optimization, and model/runtime co-optimization, alongside inference engines and distributed inference architectures. You will investigate how these approaches interact, evaluate their trade-offs across model quality, latency, throughput, memory footprint, and cost per token, and work with engineering teams to bring promising results into production. Your responsibilities Lead research projects in efficient LLM and VLM inference, from hypotheses and experiments through ablations, prototypes, and production handoff. Develop and evaluate methods spanning quantization, quantization-aware training (QAT), distillation, speculative decoding, KV-cache reuse, KV-cache compression, long-context inference, MoE routing, and model/runtime co-optimization. Build prototypes using PyTorch, Triton, CUDA-adjacent tooling, or inference-serving frameworks, and collaborate with MLEs and platform engineers to turn them into production components. Research LLM request routing and scheduling strategies, including cache-aware load balancing and prefill–decode disaggregation (PDD). Evaluate how queueing, KV-cache transfer, worker placement, and prefill/decode capacity allocation affect latency, throughput, and serving cost. Investigate multi-node inference for dense and mixture-of-experts models, including wide expert parallelism (WideEP). Study expert placement, load imbalance, and computation/communication trade-offs, and use the findings to guide model and system architecture choices. Develop rigorous evaluations covering quality, latency, throughput, numerical stability, memory footprint, tail latency, and cost per token. Compare serving architectures under consistent workload conditions and GPU budgets. Work with MLE, GPU kernel, backend infrastructure, product, and customer teams to select research priorities with measurable production impact. Share results through internal reports, technical blogs, papers, and open-source artifacts, and mentor engineers and scientists on experimental design, scientific rigor, and model/system trade-offs. Must-haves A PhD in computer science, machine learning, ML systems, computer systems, computer architecture, electrical engineering, applied mathematics, or a closely related discipline. A strong publication record or equivalent research artifacts in ML, ML systems, efficient inference, model compression, quantization, distillation, serving systems, or related areas. Strong Python and PyTorch implementation skills, with the ability to turn ideas into experiments and working prototypes. Deep knowledge of LLMs, VLMs, transformer inference, decoding algorithms, model compression, quantization, and production-serving trade-offs. Strong experimental design skills covering ablations, baselines, metrics, statistical reasoning, and failure analysis. Excellent written and verbal communication. Nice-to-haves First-author publications at venues such as NeurIPS, ICML, ICLR, MLSys, ACL, EMNLP, ASPLOS, OSDI, SOSP, ISCA, or HPCA. Experience deploying ML models or inference optimizations in production. Experience with vLLM, SGLang, TensorRT-LLM, NVIDIA Dynamo, FlashAttention, FlashInfer, Triton, CUDA, or PyTorch internals. Experience applying post-training, SFT, DPO, RLHF, RLAIF, preference optimization, or synthetic data generation to inference quality or efficiency. Open-source research artifacts, widely used benchmarks, technical blogs, or invited talks demonstrating contributions to efficient AI systems. Research or implementation experience in one or more areas of distributed inference system architecture, such as LLM request routing, PDD, multi-node serving, or MoE expert parallelism, including WideEP. Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

Location: Kuala Lumpur, Malaysia; Indonesia; Singapore Workplace: fully We're Osome - an international fintech startup making the lives of entrepreneurs easier. We help thousands of businesses kick admin, accounting and bookkeeping out of their day-to-day, so they can spend more time on what's important to them. We've developed a unique solution that combines SaaS with a human-in-the-loop approach to provide full-fledged services in real-time. We’re experiencing rapid growth in both client base and team, which now comprises around 500 people across our offices worldwide. As we continue to scale, we’re looking for more bright minds who are excited to make a real impact by solving complex problems. What to expect: Intelligence builds the AI capabilities no single team at Osome should carry alone, and helps every other team ship AI well. It works in three modes. It owns cross-cutting capability. It enables product teams by pairing with their engineers, so the pattern transfers and the team runs it afterwards. It incubates only by exception: building inside another team's area when that team has no capacity, always with a written hand-back plan. This is a hands-on PM role. You'll find problems by talking to end users, dig into the data in BigQuery and Postgres to prioritise, prototype cheaply before committing engineering effort, and ship small fixes yourself. You'll also be the team's main liaison with Operations. At a glance You'd own: client and agent assistants (e.g. Maria, our client-facing bot, and the workflows it runs), document and accounting intelligence (e.g. document recognition, AI accounts review, our XBRL agent), and the shared AI foundation (evaluation and safety, memory, Osome MCP and model choices). You'd work with: five engineers, plus shared design and an analyst. Product teams across Osome and our operations teams are your customers. The problem to solve: AI is spreading across our teams faster than shared standards are. Your job is to stop every team reinventing evaluation, safety and memory, while our core AI products keep improving quarter on quarter. What you'll do: Own the Intelligence roadmap, OKRs and delivery, with two or three big bets each quarter. You make the prioritisation calls, own the business outcome behind the backlog, and write the release notes when things ship. Set the evaluation bar for AI across Osome: eval datasets, confidence thresholds, human-review sampling and go/no-go gates. With our Security team, set the safety and data-handling bar for AI across Osome: escalation rules, pre-action checks on agents, fail-open vs fail-closed behaviour, privacy and retention, client data isolation, and provider governance (e.g. zero data retention agreements). Define the success metrics for each AI product before it ships, then keep checking the data yourself after launch to see whether it's working. Brief the analyst on what to build, and review the result. Use that evidence to make model and provider calls, e.g. benchmark a new model against our own labelled documents before switching. Break epics into clear stories and tasks that engineers can pick up without a meeting. Pair with product teams' engineers to build AI features, and define what "successfully handed over" means. Be the team's liaison with Operations: run training and feedback rounds, collect baseline data, and drive adoption until the AI version beats the manual process. Run a small research track: test new techniques and approaches (e.g. retrieval, memory or agent patterns) on our own problems, and write up what we should adopt and what we should skip. Represent this team's priorities to senior stakeholders. As the team grows, mentor other PMs and help manage them. Who you are: Evaluated against our PM capability framework. At the Senior PM level, that means: Strategic impact: you can define and drive a strategy spanning 12 months or more for a platform-style team whose customers are other teams, tied to a company-level goal such as gross margin. Domain ownership: you own the OKRs, roadmap and business outcome of a complex, ambiguous, cross-functional area. You understand applied LLM/ML products deeply (evaluation, retrieval, memory, agent safety), and can become credible in our accounting and operations domain within two quarters. Collaboration: you drive high adoption of new tools with operations teams, including the processes needed to run them. You build consensus among senior leaders with conflicting goals, and you can say no while leaving the stakeholder feeling heard. Problem-solving: you map ambiguous, system-level problems, and know when a rule, a classifier or an LLM is the right tool. Execution: you reliably ship complex, cross-functional launches involving Operations and other product teams. You prototype to de-risk before committing engineering time, and you spot risks early. AI-literacy: hands-on well beyond prompting. You build prototypes and ship small PRs with AI coding tools, build eval datasets and run model experiments, read traces, and judge where models fail. Leadership: you shape direction across teams you don't manage, improve how the team works, and are ready to mentor at least one other PM as a player-coach. What you bring AI/ML features shipped to production, with quality measured after launch (accuracy, coverage, deflection). Experience building evaluation datasets and running model experiments: thresholds, go/no-go gates, human-in-the-loop decisions, and reading traces in an observability tool (we use Langfuse) to see where models fail. Experience shipping AI features that handle sensitive or financial data, and deciding when they should escalate to a human or stop. Daily use of AI coding tools (e.g. Claude Code, Codex, Cursor) to read code and ship small changes. Strong SQL. You can pick the right metrics for a product and explain what you need to an analyst. Data modelling is not required. Experience working directly with operations teams: running training, collecting feedback, and proving time saved against a manual baseline. A track record of good calls under ambiguity, and of checking afterwards whether they were right. (Nice to have) Setting company-wide safety and data-handling rules for AI: fail-open vs fail-closed policies, privacy and retention, and client data isolation, including knowing when a new AI vendor needs a security review before it sees any data. (Nice to have) Bookkeeping or accounting literacy: enough double-entry, chart-of-accounts and GST/VAT knowledge to judge whether an AI accounts review or document check is right. Either a qualification or hands-on bookkeeping experience counts. (Nice to have) Document AI/OCR in production: classifying or extracting invoices, bank statements and receipts, and the trade-offs between coverage, accuracy, confidence thresholds and cost. (Nice to have) Agentic systems or MCP in production: agents or tools that take real actions, with permissions, human approval steps and multi-step evaluation. Our Benefits Multi-cultural environment to enhance your global perspective. Learning opportunities and mentorship from peers and leaders. Flexible working arrangement; Hybrid working arrangement An agile working model focused on goals and performance. Equal Opportunity Statement At OSOME, creating a culture where individuals of all backgrounds feel comfortable really matters. Everyone who applies will receive fair consideration for employment. We do not discriminate based upon race, colour, religion, sex, sexual orientation, age, marital status, gender identity, national origin, disability, or any other applicable legally protected characteristics in the location in which the candidate is applying. We want to ensure that we represent the diversity of talent in the society we live in today. If you have any accessibility requirements that would make you more comfortable during the application and interview process, please let us know so that we can support you.

Требования: • Глубокий Swift, зрелое понимание SwiftUI и UIKit (включая interop) • Concurrency на уровне проектирования: actor-изоляция, structured concurrency, Swift 6 strict concurrency • Самостоятельные исследования производительности до измеримого результата • Профилирование через Instruments, Memory Graph, MetricKit Важно: • Первые 3 дня обязательно в офисе (Москва) для получения техники и онбординга О компании: AI-продукт Сбера: мобильное приложение со стримингом контента, современный стек без legacy. Условия: • Занятость full time, 2 месяца с возможным продлением.

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 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.

Location: Singapore, Singapore OKX will be prioritising applicants who have a current right to work in Singapore, and do not require OKX's sponsorship of a visa. 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 Mobile Engineers to join our Compliance engineering team. In this role, you will build secure, regulation-compliant, and high-trust mobile solutions that power global onboarding, identity verification, risk control, and regulatory compliance systems. We are open to candidates across a wide spectrum of experience. Whether you are an engineer early in your career eager to master mobile security and regulatory technology, or a seasoned practitioner who can architect resilient systems and drive technical direction across global markets, you will find high impact and technical depth here. You should be self-driven, hungry to grow, and motivated by solving critical real-world engineering challenges. What You'll Be Doing Build, maintain, and scale native iOS features and user flows using Swift and modern iOS frameworks. Collaborate with Product, Design, and Backend Engineering to translate functional requirements into smooth, responsive mobile experiences. Integrate third-party SDKs, native frameworks, and hardware capabilities (such as camera APIs, biometrics, or local security features) with a focus on UX and performance. Contribute to mobile client architecture, keeping the codebase modular, testable, and maintainable. Participate in code reviews, testing, and continuous optimization to maintain high iOS engineering standards. Leverage modern development tools and AI coding assistants to streamline your daily workflow and accelerate delivery. Diagnose and fix edge cases, performance bottlenecks, and production bugs to ensure a rock-solid iOS app experience. What We Look For In You Hands-on native iOS engineering experience with Swift, SwiftUI, and UIKit . Solid grasp of software engineering principles, memory management, multithreading, and mobile system design. Experience integrating RESTful APIs into production iOS applications. Commitment to writing clean, well-tested, and maintainable code. Strong problem-solving mindset with a desire to build high-quality software. Openness to using modern developer tools and AI coding assistants (e.g., Claude Code, Codex) in your everyday coding workflow. Nice-To-Haves Exposure to mobile CI/CD pipelines (e.g., Fastlane, GitHub Actions, Xcode Cloud). Experience working with modular iOS architectures or building internal shared SDKs/frameworks. Familiarity with unit testing frameworks (XCTest) and UI testing on iOS. Experience with feature flagging, analytics, or A/B experimentation frameworks. 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! #LI-ML1 #LI-ONSITE 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 .

Кого ищем: — Человека, полностью соответствующего ожиданиям, а не учящегося на ходу. — Рабочие руки, а не технического менеджера. Кто не подойдёт: — Кандидаты с преобладающим или последним опытом в роли технических менеджеров: Team Lead, CTO и т.п. — Кандидаты с преобладающим или последним опытом работы на фрилансе или в аутсорсинг-компаниях. — Кандидаты с преобладающим или последним опытом в роли Frontend / Fullstack-разработчиков. Мы ожидаем: — Опыт от 8 лет в роли Backend-разработчика (не Fullstack). — Опыт работы от 6 лет с Node.js и TypeScript: event loop, streams, memory management. — Опыт работы с контейнеризацией и оркестрацией Kubernetes от 3 лет. — Опыт работы от 2 лет с AWS: EKS, RDS, DynamoDB, S3. — Опыт работы от 1 года с гибридным хранилищем: MySQL, Redis, MongoDB, DynamoDB – каждая БД под свою задачу. — Обязательный опыт использования LLM в работе. Чем предстоит заниматься: — Разработка и развитие backend-сервисов на NestJS. — Проектирование и реализация API и межсервисных взаимодействий. — Деплой и эксплуатация сервисов в Kubernetes. — Работа с асинхронными сценариями (RabbitMQ). — Использование Redis для кэширования и pub/sub. — Работа с базами данных MySQL, MongoDB, DynamoDB. — Работа с облачной инфраструктурой AWS (эксплуатация и развитие backend-сервисов). Условия: — Полностью удалённый формат работы. — Оплачиваемый отпуск 28 календарных дней. — 100% оплата больничного. — Работа в продуктовой IT-компании.

Location: Tashkent, Uzbekistan We are looking for Engineers experienced in Unreal Engine to work on AAA game titles. Join us if you would like to raise your expertise by completing challenging tasks with the help from experts in game development. Being a developer in our company means: Working in different areas (e.g. Gameplay, AI, Engine), making new features and supporting the existing ones. Meeting interesting people from different areas of game development. Supporting different platforms and stores from Sony, Microsoft, Nintendo and others. Participating in architectural decisions, design of new systems and modules, or prototyping new features. Performance optimizations. Going through each stage of the game development pipeline and release of the game. Requirements Commercial experience with C++ and Unreal Engine 4 or 5. Experience with popular subsystems, e.g. Gameplay Ability System, Behavior Trees, UMG. Comprehension of Unreal Engine memory management model. Good understanding of dynamic polymorphism and C++ specific notions. Practical knowledge with Blueprint scripting. Good communication skills and fluent spoken English. Benefits Cooperating with an international team of world-class professionals on exciting and challenging projects Learning & Development opportunities – mentoring, lectures, participation at industry conferences and events

Location: Astana, Kazakhstan We are looking for Engineers experienced in Unreal Engine to work on AAA game titles. Join us if you would like to raise your expertise by completing challenging tasks with the help from experts in game development. Being a developer in our company means: Working in different areas (e.g. Gameplay, AI, Engine), making new features and supporting the existing ones. Meeting interesting people from different areas of game development. Supporting different platforms and stores from Sony, Microsoft, Nintendo and others. Participating in architectural decisions, design of new systems and modules, or prototyping new features. Performance optimizations. Going through each stage of the game development pipeline and release of the game. Requirements Commercial experience with C++ and Unreal Engine 4 or 5. Experience with popular subsystems, e.g. Gameplay Ability System, Behavior Trees, UMG. Comprehension of Unreal Engine memory management model. Good understanding of dynamic polymorphism and C++ specific notions. Practical knowledge with Blueprint scripting. Good communication skills and fluent spoken English. Benefits Cooperating with an international team of world-class professionals on exciting and challenging projects Learning & Development opportunities – mentoring, lectures, participation at industry conferences and events

Location: Amsterdam Workplace: Remote ABOUT US At LangChain, our mission is to enable every company to own its intelligence. We believe agents will transform how companies operate, and we're building the foundation to make that future possible. Our open-source harnesses and LangSmith platform give developers and enterprises the infrastructure to run, improve, and govern agents at scale. We've raised $460M to date, with our most recent funding round valuing the company at $3B, backed by leading investors including Sequoia, Benchmark, IVP, and CapitalG. As we continue to expand our platform and tackle some of the hardest challenges in agent engineering, every team member has the opportunity to make a meaningful impact and help shape both our technology and the future of the industry. More than 7,000 organizations rely on LangSmith, from fast-growing startups to Fortune 500 enterprises, including NVIDIA, Bridgewater, LinkedIn, Workday, and Rippling. We're just getting started on making high-performing agents easier to build and manage at scale. ABOUT THE ROLE: We're looking for a Deployed Architect to join our Professional Services team. You'll work directly with enterprise customers to design, deploy, and optimize production-grade AI infrastructure and agent systems. You'll be responsible for architecting scalable, secure infrastructure deployments and building reliable, well-evaluated agent applications that solve real business problems. This role combines software development, infrastructure/platform engineering, and customer-facing skills. You'll work on everything from Kubernetes cluster design to multi-agent system architecture, requiring deep technical expertise across both infrastructure and agent engineering domains. This role offers direct impact on customer success, the opportunity to shape best practices, and work with cutting-edge AI technology. You'll join a collaborative team environment with a strong engineering culture. WHAT YOU'LL DO: - Infrastructure & Platform Engineering: Design scalable, highly-available infrastructure for AI platform deployments (compute, storage, networking, security), enterprise integration patterns, Infrastructure as Code (Terraform, Helm), multi-region HA/DR strategies, and CI/CD pipelines - Agent Engineering & Development: Design multi-agent systems using different patterns, implement agent logic using modern frameworks (langchain/langgraph), design comprehensive evaluation frameworks, optimize prompts with A/B testing, and guide deployment/operations - Customer Engagement & Assessment: Lead technical maturity assessments, work directly with enterprise customers to understand requirements and present recommendations, and partner with Engagement Managers and Product/Engineering teams WHAT YOU'LL BRING: 7+ years of experience in a technical, hands-on customer-facing roles such as Solutions Architect, Deployed Architect or Forward Deployed Engineer. We also like former founders, so if you have an unusual background, but all the right skillsets, you are welcome to apply Infrastructure & Platform: - 3+ years of experience designing and deploying production infrastructure on cloud platforms (GCP, AWS, or Azure) - Strong Kubernetes experience (GKE, EKS, or AKS) including cluster design, autoscaling, and multi-zone deployments - Experience with Infrastructure as Code (Terraform, Helm) and GitOps practices - Knowledge of database systems (relational databases, in-memory data stores) including HA, replication, backup strategies, and sizing - Experience designing high-availability and disaster recovery solutions - Strong understanding of networking, security (SSO/RBAC, TLS, secrets management), and observability (Prometheus, Grafana, Datadog) - Experience with CI/CD pipelines for infrastructure and applications Agent Engineering & Development: - 1+ years of experience building production AI/ML applications or agents - Strong experience with LLM frameworks (LangChain, LangGraph, or similar) for building agent-based applications - Experience with state management patterns (short-term and long-term memory) - Experience designing and implementing evaluation frameworks for AI applications - Strong prompt engineering skills with experience in optimization and A/B testing - Experience with vector stores, RAG patterns, and knowledge organization - Experience with tool integration, API design, and error handling patterns - Strong Python and/or TypeScript development skills Customer-Facing: - Customer-facing experience with enterprise customers - Experience conducting technical assessments or infrastructure audits - Strong communication skills with ability to explain technical concepts to diverse audiences KEY ATTRIBUTES: - Strong problem-solving skills with ability to analyze complex requirements and design elegant solutions - Excellent customer-facing communication skills, able to explain technical concepts to diverse audiences - Experience working cross-functionally with engineering teams, product teams, and customers - Consultative approach with ability to understand customer needs, provide recommendations, and guide implementation - Ability to balance infrastructure architecture with agent development work - Strong engineering background with hands-on development experience COMPENSATION: €110,000-€185,000 base salary + equity Location: - Netherlands, Amsterdam - Remote with up to 25% travel COMPENSATION PHILOSOPHY: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. We are hiring for this role across a range of scope, and the compensation band reflects that. Your offer depends on what we learn about your impact, craft, leadership, and communication during the interview process. We will tell you early where you’re tracking and talk comp with you before offer stage. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. BENEFITS Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

Location: London Workplace: Remote ABOUT US At LangChain, our mission is to enable every company to own its intelligence. We believe agents will transform how companies operate, and we're building the foundation to make that future possible. Our open-source harnesses and LangSmith platform give developers and enterprises the infrastructure to run, improve, and govern agents at scale. We've raised $460M to date, with our most recent funding round valuing the company at $3B, backed by leading investors including Sequoia, Benchmark, IVP, and CapitalG. As we continue to expand our platform and tackle some of the hardest challenges in agent engineering, every team member has the opportunity to make a meaningful impact and help shape both our technology and the future of the industry. More than 7,000 organizations rely on LangSmith, from fast-growing startups to Fortune 500 enterprises, including NVIDIA, Bridgewater, LinkedIn, Workday, and Rippling. We're just getting started on making high-performing agents easier to build and manage at scale. ABOUT THE ROLE: We're looking for a Deployed Architect to join our Professional Services team. You'll work directly with enterprise customers to design, deploy, and optimize production-grade AI infrastructure and agent systems. You'll be responsible for architecting scalable, secure infrastructure deployments and building reliable, well-evaluated agent applications that solve real business problems. This role combines software development, infrastructure/platform engineering, and customer-facing skills. You'll work on everything from Kubernetes cluster design to multi-agent system architecture, requiring deep technical expertise across both infrastructure and agent engineering domains. This role offers direct impact on customer success, the opportunity to shape best practices, and work with cutting-edge AI technology. You'll join a collaborative team environment with a strong engineering culture. WHAT YOU'LL DO: - Infrastructure & Platform Engineering: Design scalable, highly-available infrastructure for AI platform deployments (compute, storage, networking, security), enterprise integration patterns, Infrastructure as Code (Terraform, Helm), multi-region HA/DR strategies, and CI/CD pipelines - Agent Engineering & Development: Design multi-agent systems using different patterns, implement agent logic using modern frameworks (langchain/langgraph), design comprehensive evaluation frameworks, optimize prompts with A/B testing, and guide deployment/operations - Customer Engagement & Assessment: Lead technical maturity assessments, work directly with enterprise customers to understand requirements and present recommendations, and partner with Engagement Managers and Product/Engineering teams WHAT YOU'LL BRING: 7+ years of experience in a technical, hands-on customer-facing roles such as Solutions Architect, Deployed Architect or Forward Deployed Engineer. We also like former founders, so if you have an unusual background, but all the right skillsets, you are welcome to apply Infrastructure & Platform: - 3+ years of experience designing and deploying production infrastructure on cloud platforms (GCP, AWS, or Azure) - Strong Kubernetes experience (GKE, EKS, or AKS) including cluster design, autoscaling, and multi-zone deployments - Experience with Infrastructure as Code (Terraform, Helm) and GitOps practices - Knowledge of database systems (relational databases, in-memory data stores) including HA, replication, backup strategies, and sizing - Experience designing high-availability and disaster recovery solutions - Strong understanding of networking, security (SSO/RBAC, TLS, secrets management), and observability (Prometheus, Grafana, Datadog) - Experience with CI/CD pipelines for infrastructure and applications Agent Engineering & Development: - 1+ years of experience building production AI/ML applications or agents - Strong experience with LLM frameworks (LangChain, LangGraph, or similar) for building agent-based applications - Experience with state management patterns (short-term and long-term memory) - Experience designing and implementing evaluation frameworks for AI applications - Strong prompt engineering skills with experience in optimization and A/B testing - Experience with vector stores, RAG patterns, and knowledge organization - Experience with tool integration, API design, and error handling patterns - Strong Python and/or TypeScript development skills Customer-Facing: - Customer-facing experience with enterprise customers - Experience conducting technical assessments or infrastructure audits - Strong communication skills with ability to explain technical concepts to diverse audiences KEY ATTRIBUTES: - Strong problem-solving skills with ability to analyze complex requirements and design elegant solutions - Excellent customer-facing communication skills, able to explain technical concepts to diverse audiences - Experience working cross-functionally with engineering teams, product teams, and customers - Consultative approach with ability to understand customer needs, provide recommendations, and guide implementation - Ability to balance infrastructure architecture with agent development work - Strong engineering background with hands-on development experience COMPENSATION: £100,000-£165,000 base salary + equity Location: - UK, London - Remote with up to 25% travel COMPENSATION PHILOSOPHY: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. We are hiring for this role across a range of scope, and the compensation band reflects that. Your offer depends on what we learn about your impact, craft, leadership, and communication during the interview process. We will tell you early where you’re tracking and talk comp with you before offer stage. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. BENEFITS Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

Location: Remote - Singapore Workplace: Remote ABOUT US At LangChain, our mission is to enable every company to own its intelligence. We believe agents will transform how companies operate, and we're building the foundation to make that future possible. Our open-source harnesses and LangSmith platform give developers and enterprises the infrastructure to run, improve, and govern agents at scale. We've raised $460M to date, with our most recent funding round valuing the company at $3B, backed by leading investors including Sequoia, Benchmark, IVP, and CapitalG. As we continue to expand our platform and tackle some of the hardest challenges in agent engineering, every team member has the opportunity to make a meaningful impact and help shape both our technology and the future of the industry. More than 7,000 organizations rely on LangSmith, from fast-growing startups to Fortune 500 enterprises, including NVIDIA, Bridgewater, LinkedIn, Workday, and Rippling. We're just getting started on making high-performing agents easier to build and manage at scale. ABOUT THE ROLE: We're looking for a Deployed Architect to join our Professional Services team. You'll work directly with enterprise customers to design, deploy, and optimize production-grade AI infrastructure and agent systems. You'll be responsible for architecting scalable, secure infrastructure deployments and building reliable, well-evaluated agent applications that solve real business problems. This role combines software development, infrastructure/platform engineering, and customer-facing skills. You'll work on everything from Kubernetes cluster design to multi-agent system architecture, requiring deep technical expertise across both infrastructure and agent engineering domains. This role offers direct impact on customer success, the opportunity to shape best practices, and work with cutting-edge AI technology. You'll join a collaborative team environment with a strong engineering culture. KEY RESPONSIBILITIES: - Infrastructure & Platform Engineering: Design scalable, highly-available infrastructure for AI platform deployments (compute, storage, networking, security), enterprise integration patterns, Infrastructure as Code (Terraform, Helm), multi-region HA/DR strategies, and CI/CD pipelines - Agent Engineering & Development: Design multi-agent systems using different patterns, implement agent logic using modern frameworks (langchain/langgraph), design comprehensive evaluation frameworks, optimize prompts with A/B testing, and guide deployment/operations - Customer Engagement & Assessment: Lead technical maturity assessments, work directly with enterprise customers to understand requirements and present recommendations, and partner with Engagement Managers and Product/Engineering teams WHAT WE'RE LOOKING FOR REQUIRED EXPERIENCE 7+ years of experience in a technical, hands-on customer-facing roles such as Solutions Architect, Deployed Architect or Forward Deployed Engineer. We also like former founders, so if you have an unusual background, but all the right skillsets, you are welcome to apply Infrastructure & Platform: - 3+ years of experience designing and deploying production infrastructure on cloud platforms (GCP, AWS, or Azure) - Strong Kubernetes experience (GKE, EKS, or AKS) including cluster design, autoscaling, and multi-zone deployments - Experience with Infrastructure as Code (Terraform, Helm) and GitOps practices - Knowledge of database systems (relational databases, in-memory data stores) including HA, replication, backup strategies, and sizing - Experience designing high-availability and disaster recovery solutions - Strong understanding of networking, security (SSO/RBAC, TLS, secrets management), and observability (Prometheus, Grafana, Datadog) - Experience with CI/CD pipelines for infrastructure and applications Agent Engineering & Development: - 1+ years of experience building production AI/ML applications or agents - Strong experience with LLM frameworks (LangChain, LangGraph, or similar) for building agent-based applications - Experience with state management patterns (short-term and long-term memory) - Experience designing and implementing evaluation frameworks for AI applications - Strong prompt engineering skills with experience in optimization and A/B testing - Experience with vector stores, RAG patterns, and knowledge organization - Experience with tool integration, API design, and error handling patterns - Strong Python and/or TypeScript development skills Customer-Facing: - Customer-facing experience with enterprise customers - Experience conducting technical assessments or infrastructure audits - Strong communication skills with ability to explain technical concepts to diverse audiences KEY ATTRIBUTES: - Strong problem-solving skills with ability to analyze complex requirements and design elegant solutions - Excellent customer-facing communication skills, able to explain technical concepts to diverse audiences - Experience working cross-functionally with engineering teams, product teams, and customers - Consultative approach with ability to understand customer needs, provide recommendations, and guide implementation - Ability to balance infrastructure architecture with agent development work - Strong engineering background with hands-on development experience COMPENSATION: $185,000-$260,000 base salary + equity Location: - Singapore - Remote with up to 25% travel COMPENSATION PHILOSOPHY: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. We are hiring for this role across a range of scope, and the compensation band reflects that. Your offer depends on what we learn about your impact, craft, leadership, and communication during the interview process. We will tell you early where you’re tracking and talk comp with you before offer stage. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. BENEFITS Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

Location: Remote - Singapore Workplace: Remote ABOUT US At LangChain, our mission is to enable every company to own its intelligence. We believe agents will transform how companies operate, and we're building the foundation to make that future possible. Our open-source harnesses and LangSmith platform give developers and enterprises the infrastructure to run, improve, and govern agents at scale. We've raised $460M to date, with our most recent funding round valuing the company at $3B, backed by leading investors including Sequoia, Benchmark, IVP, and CapitalG. As we continue to expand our platform and tackle some of the hardest challenges in agent engineering, every team member has the opportunity to make a meaningful impact and help shape both our technology and the future of the industry. More than 7,000 organizations rely on LangSmith, from fast-growing startups to Fortune 500 enterprises, including NVIDIA, Bridgewater, LinkedIn, Workday, and Rippling. We're just getting started on making high-performing agents easier to build and manage at scale. ABOUT THE ROLE: We're looking for a Deployed Engineer to join our Professional Services team, working directly with enterprise customers to build reliable, production agents. You'll translate vague enterprise workflows into concrete software specs and guide engineering teams through the resulting solution, or build it for them. You might spend a week designing a customer's agent architecture, a few weeks co-building their evaluation pipeline, or a quarter embedded inside their team shipping alongside their engineers. You are someone who's built real AI systems for production and can defend the technical tradeoffs within them. KEY RESPONSIBILITIES: - Advising: Agent architecture design, evaluation strategy review, and best-practice production guidance. - Building: Co-build with the customer's engineering team across the full Agent Development Lifecycle (ADLC) in outcome-scoped engagements. - Embedding: Serve as a deployed engineer inside the customer's team for extended engagements, operating as a de facto member of their org to ship agent systems directly. - Agent Engineering: ADLC end-to-end, architecture design, orchestration patterns, evals, custom conversational UIs, and production deployment. - Applied AI: Post-training, supervised fine-tuning, harness engineering, trace mining, model selection and evaluation methodology. REQUIREMENTS: - 4+ years of software engineering experience with deep expertise in Python. TypeScript/JavaScript a plus. - 2+ years of hands-on experience building and shipping production agent systems. - Strong client-facing communication skills, with the ability to confidently articulate architectural decisions to technical stakeholders (engineers, architects, CTOs). - Strong experience with LangChain/LangGraph/Deep Agents or comparable frameworks, including multi-agent patterns and state management (short and long-term memory). - Deep familiarity designing and implementing evaluation methodologies for non-deterministic AI systems. - Comfortable operating across the full spectrum from advisory to embedded delivery. - Willing to travel up to 20% of the time. NICE TO HAVE: - Exposure to dataset curation and post-training techniques (SFT, DPO, RLHF) on open-weight models using tools like Axolotl, Unsloth, Hugging Face transformers, or TRL. - Experience with trace mining to drive continuous improvement loops COMPENSATION: $185,000-$260,000 base salary + equity Location: - Singapore - Remote with up to 25% travel Looking to lead technical strategy across the customer journey from Proofs of Value (PoVs) to driving overall adoption? Please check out the Deployed Engineer listing focused on Account Strategy & Solutions. COMPENSATION PHILOSOPHY: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. We are hiring for this role across a range of scope, and the compensation band reflects that. Your offer depends on what we learn about your impact, craft, leadership, and communication during the interview process. We will tell you early where you’re tracking and talk comp with you before offer stage. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. BENEFITS Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

About the job: QV.AC is a general purpose AI assistant that runs locally on your devices, giving people real control over their data and AI usage without cloud dependency or data harvesting. The focus is on local, on-device, privacy-preserving AI connected across Tether's peer-to-peer ecosystem. Responsibilities: Engineering: — Run the app and feature teams day to day: unblocking, reviewing, and keeping them shipping. — Set and hold a high engineering bar for performance, reliability, and clean APIs. — Own the technical design of features and the API surface between the AI core and the app. — Ensure close collaboration with AI research and deep tech teams on code reviews, design, and anything involving models or inference. Product Partnership: — Work alongside product managers to turn vision and roadmap into scoped, buildable work. — Push back when scope and reality don't match and propose better paths. — Bring an engineering perspective to product decisions, especially regarding local AI model capabilities and limitations. — Help the team move fast using AI tools and quick prototypes to validate ideas before commitment. Leadership: — Create clarity around team goals and define success. — Mentor team leads to build strong operating systems, improve collaboration, and grow as leaders. — Lead by example: actively contribute when needed and step back when teams are ready to own their work. Mandatory Requirements: — Experience managing engineers or engineering leads who ship consumer products, ideally AI-powered apps. — Strong product sense to distinguish good features from busywork. — Intuition for applied AI and on-device constraints such as model size, latency, memory, battery, and the gap between demos and reliable features. — Heavy use of AI tools in own work and enthusiasm for experimenting with new models and capabilities. — Deep knowledge of JavaScript and React. — Initiative, curiosity, resilience, and ability to give and receive direct critique. Preferred: — Experience with local or on-device inference, LLM evaluations, cross-platform mobile and desktop apps, or open source. Work format: — Remote work from anywhere in the world. Additional information: — Recruitment scams warning and official application channels provided. — Official careers page: https://tether.recruitee.com/ — Communication only via official company emails ending with @tether.to or @tether.io. — No requests for payment or financial details during hiring. — Candidates encouraged to mention the word EXTOLL when applying to confirm they read the job post fully.

Location: New York, NY Workplace: OnSite ABOUT US At LangChain, our mission is to enable every company to own its intelligence. We believe agents will transform how companies operate, and we're building the foundation to make that future possible. Our open-source harnesses and LangSmith platform give developers and enterprises the infrastructure to run, improve, and govern agents at scale. We've raised $460M to date, with our most recent funding round valuing the company at $3B, backed by leading investors including Sequoia, Benchmark, IVP, and CapitalG. As we continue to expand our platform and tackle some of the hardest challenges in agent engineering, every team member has the opportunity to make a meaningful impact and help shape both our technology and the future of the industry. More than 7,000 organizations rely on LangSmith, from fast-growing startups to Fortune 500 enterprises, including NVIDIA, Bridgewater, LinkedIn, Workday, and Rippling. We're just getting started on making high-performing agents easier to build and manage at scale. ABOUT THE ROLE We're looking for a Deployed Architect to join our Professional Services team. You'll work directly with enterprise customers to design, deploy, and optimize production-grade AI infrastructure and agent systems. You'll be responsible for architecting scalable, secure infrastructure deployments and building reliable, well-evaluated agent applications that solve real business problems. This role combines software development, infrastructure/platform engineering, and customer-facing skills. You'll work on everything from Kubernetes cluster design to multi-agent system architecture, requiring deep technical expertise across both infrastructure and agent engineering domains. This role offers direct impact on customer success, the opportunity to shape best practices, and work with cutting-edge AI technology. You'll join a collaborative team environment with a strong engineering culture. KEY RESPONSIBILITIES - Infrastructure & Platform Engineering: Design scalable, highly-available infrastructure for AI platform deployments (compute, storage, networking, security), enterprise integration patterns, Infrastructure as Code (Terraform, Helm), multi-region HA/DR strategies, and CI/CD pipelines - Agent Engineering & Development: Design multi-agent systems using different patterns, implement agent logic using modern frameworks (langchain/langgraph), design comprehensive evaluation frameworks, optimize prompts with A/B testing, and guide deployment/operations - Customer Engagement & Assessment: Lead technical maturity assessments, work directly with enterprise customers to understand requirements and present recommendations, and partner with Engagement Managers and Product/Engineering teams WHAT WE'RE LOOKING FOR REQUIRED EXPERIENCE 7+ years of experience in a technical, hands-on customer-facing roles such as Solutions Architect or Forward Deployed Engineer. We also like former founders, so if you have an unusual background, but all the right skillsets, you are welcome to apply Infrastructure & Platform: - 3+ years of experience designing and deploying production infrastructure on cloud platforms (GCP, AWS, or Azure) - Strong Kubernetes experience (GKE, EKS, or AKS) including cluster design, autoscaling, and multi-zone deployments - Experience with Infrastructure as Code (Terraform, Helm) and GitOps practices - Knowledge of database systems (relational databases, in-memory data stores) including HA, replication, backup strategies, and sizing - Experience designing high-availability and disaster recovery solutions - Strong understanding of networking, security (SSO/RBAC, TLS, secrets management), and observability (Prometheus, Grafana, Datadog) - Experience with CI/CD pipelines for infrastructure and applications Agent Engineering & Development: - 1+ years of experience building production AI/ML applications or agents - Strong experience with LLM frameworks (LangChain, LangGraph, or similar) for building agent-based applications - Experience with state management patterns (short-term and long-term memory) - Experience designing and implementing evaluation frameworks for AI applications - Strong prompt engineering skills with experience in optimization and A/B testing - Experience with vector stores, RAG patterns, and knowledge organization - Experience with tool integration, API design, and error handling patterns - Strong Python and/or TypeScript development skills Customer-Facing: - Customer-facing experience with enterprise customers - Experience conducting technical assessments or infrastructure audits - Strong communication skills with ability to explain technical concepts to diverse audiences KEY ATTRIBUTES - Strong problem-solving skills with ability to analyze complex requirements and design elegant solutions - Excellent customer-facing communication skills, able to explain technical concepts to diverse audiences - Experience working cross-functionally with engineering teams, product teams, and customers - Consultative approach with ability to understand customer needs, provide recommendations, and guide implementation - Ability to balance infrastructure architecture with agent development work - Strong engineering background with hands-on development experience - Willing to travel up to 20% of the time Location: New York City Compensation: $170,000-$300,000 base salary + equity Looking to lead technical strategy across the customer journey from Proofs of Value (PoVs) to driving overall adoption? Please check out the Deployed Engineer listing focused on Account Strategy & Solutions. COMPENSATION PHILOSOPHY: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. We are hiring for this role across a range of scope, and the compensation band reflects that. Your offer depends on what we learn about your impact, craft, leadership, and communication during the interview process. We will tell you early where you’re tracking and talk comp with you before offer stage. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. BENEFITS Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

Location: Austin, TX Workplace: Remote ABOUT US At LangChain, our mission is to enable every company to own its intelligence. We believe agents will transform how companies operate, and we're building the foundation to make that future possible. Our open-source harnesses and LangSmith platform give developers and enterprises the infrastructure to run, improve, and govern agents at scale. We've raised $460M to date, with our most recent funding round valuing the company at $3B, backed by leading investors including Sequoia, Benchmark, IVP, and CapitalG. As we continue to expand our platform and tackle some of the hardest challenges in agent engineering, every team member has the opportunity to make a meaningful impact and help shape both our technology and the future of the industry. More than 7,000 organizations rely on LangSmith, from fast-growing startups to Fortune 500 enterprises, including NVIDIA, Bridgewater, LinkedIn, Workday, and Rippling. We're just getting started on making high-performing agents easier to build and manage at scale. ABOUT THE ROLE We're looking for a Deployed Architect to join our Professional Services team. You'll work directly with enterprise customers to design, deploy, and optimize production-grade AI infrastructure and agent systems. You'll be responsible for architecting scalable, secure infrastructure deployments and building reliable, well-evaluated agent applications that solve real business problems. This role combines software development, infrastructure/platform engineering, and customer-facing skills. You'll work on everything from Kubernetes cluster design to multi-agent system architecture, requiring deep technical expertise across both infrastructure and agent engineering domains. This role offers direct impact on customer success, the opportunity to shape best practices, and work with cutting-edge AI technology. You'll join a collaborative team environment with a strong engineering culture. KEY RESPONSIBILITIES - Infrastructure & Platform Engineering: Design scalable, highly-available infrastructure for AI platform deployments (compute, storage, networking, security), enterprise integration patterns, Infrastructure as Code (Terraform, Helm), multi-region HA/DR strategies, and CI/CD pipelines - Agent Engineering & Development: Design multi-agent systems using different patterns, implement agent logic using modern frameworks (langchain/langgraph), design comprehensive evaluation frameworks, optimize prompts with A/B testing, and guide deployment/operations - Customer Engagement & Assessment: Lead technical maturity assessments, work directly with enterprise customers to understand requirements and present recommendations, and partner with Engagement Managers and Product/Engineering teams WHAT WE'RE LOOKING FOR REQUIRED EXPERIENCE 7+ years of experience in a technical, hands-on customer-facing roles such as Solutions Architect or Forward Deployed Engineer. We also like former founders, so if you have an unusual background, but all the right skillsets, you are welcome to apply Infrastructure & Platform: - 3+ years of experience designing and deploying production infrastructure on cloud platforms (GCP, AWS, or Azure) - Strong Kubernetes experience (GKE, EKS, or AKS) including cluster design, autoscaling, and multi-zone deployments - Experience with Infrastructure as Code (Terraform, Helm) and GitOps practices - Knowledge of database systems (relational databases, in-memory data stores) including HA, replication, backup strategies, and sizing - Experience designing high-availability and disaster recovery solutions - Strong understanding of networking, security (SSO/RBAC, TLS, secrets management), and observability (Prometheus, Grafana, Datadog) - Experience with CI/CD pipelines for infrastructure and applications Agent Engineering & Development: - 1+ years of experience building production AI/ML applications or agents - Strong experience with LLM frameworks (LangChain, LangGraph, or similar) for building agent-based applications - Experience with state management patterns (short-term and long-term memory) - Experience designing and implementing evaluation frameworks for AI applications - Strong prompt engineering skills with experience in optimization and A/B testing - Experience with vector stores, RAG patterns, and knowledge organization - Experience with tool integration, API design, and error handling patterns - Strong Python and/or TypeScript development skills Customer-Facing: - Customer-facing experience with enterprise customers - Experience conducting technical assessments or infrastructure audits - Strong communication skills with ability to explain technical concepts to diverse audiences KEY ATTRIBUTES - Strong problem-solving skills with ability to analyze complex requirements and design elegant solutions - Excellent customer-facing communication skills, able to explain technical concepts to diverse audiences - Experience working cross-functionally with engineering teams, product teams, and customers - Consultative approach with ability to understand customer needs, provide recommendations, and guide implementation - Ability to balance infrastructure architecture with agent development work - Strong engineering background with hands-on development experience - Willing to travel up to 20% of the time Location: Austin, Texas Compensation: $170,000-$270,000 base salary + equity Looking to lead technical strategy across the customer journey from Proofs of Value (PoVs) to driving overall adoption? Please check out the Deployed Engineer listing focused on Account Strategy & Solutions. COMPENSATION PHILOSOPHY: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. We are hiring for this role across a range of scope, and the compensation band reflects that. Your offer depends on what we learn about your impact, craft, leadership, and communication during the interview process. We will tell you early where you’re tracking and talk comp with you before offer stage. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. BENEFITS Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.