Вакансии

Location: Kyiv; Remote (Ukraine) Workplace: Hybrid [https://app.ashbyhq.com/api/images/user-content/d5fc9a0c-9608-448b-b96f-2a4966f020bf/160b8b0f-7d40-4c02-9400-1b4fd1ada701/G_LINK_OWN_COVER_1.png] About us: Gismart is a value-driven mobile app developer with a strong presence in the Health & Wellness, Utilities, and Music app markets. We have achieved a significant milestone of over 1 billion downloads worldwide, taking a step toward our mission of cultivating the well-being of people worldwide. With headquarters in London, UK, Gismart is a dynamic global company with a reach extending across Europe and far beyond. Our determined team comprises over 350 individuals who bring diversity, creativity, innovation, and relentless drive to the company. Gismart unites professionals from diverse backgrounds in entertainment, music, and tech, allowing us to play to each other’s strengths and succeed as a team. Our mission: Become a stepping stone on our customers’ journeys of self-improvement. Our values: - Deliver what matters - Respect and support others - Initiate and own - Voiceopenly - Execute with quality If you are passionate about mobile app development and want to join a company that’s reshaping the industry, Gismart is the place for you. We provide exciting career opportunities, a supportive workplace culture, and the chance to contribute to a team that is making a tangible impact. For more information on Gismart, visit gismart.com http://gismart.com. About project: Spilio is a product that helps people grow through developing essential soft skills. We combine practical learning with thoughtfully curated ideas from powerful books. Spilio is designed for helping people become more confident, self-aware, and effective in their everyday lives. Requirements: - 1+ year of experience working with mobile applications - Knowledge of and hands-on experience with the latest AI tools (Kling, HeyGen, ElevenLabs, etc.) - Proficiency in Adobe After Effects - Basic knowledge of Adobe Illustrator, Photoshop, and Figma - A portfolio showcasing completed projects - Understanding of the basic principles of video editing and animation - Knowledge of Adobe After Effects plugins Would be a plus: - Experience conducting basic competitor research for creative ideas and references - Staying up to date with social media trends and continuously expanding visual awareness - Keeping up with emerging AI tools and exploring their potential for creative work Responsibilities - Design and animate performance-driven video creatives for Meta, TikTok, Google, AppLovin, and Snapchat - Collaborate with the Creative Producer and UA team on briefs, hypotheses, and rapid iterations - Adapt winning concepts into multiple variations: hooks, lengths, aspect ratios, languages, audiences - Edit footage (UGC, stock, screen captures, app gameplay) into polished, on-brand videos - Maintain visual consistency and quality at high cadence – multiple creatives per week - Use AI-powered tools to speed up production (image/video generation, voice synthesis, asset clean-up) where it makes sense - Stay current with motion trends and platform-native ad formats Employee Benefits: - Remote-First Culture: Our team is diverse and extensive, just like our product portfolio. We provide a flexible working schedule and let you work anywhere in the world, either remotely or in one of our corporate hubs - Сoworking Compensation: We provide 100% compensation for coworking spaces in Ukraine (except Kyiv, where we have a cozy and autonomous hub) and 50% compensation for coworking spaces worldwide to make sure that everyone has a comfortable and inspiring workspace - Free Office Lunches:We want you to stay fueled and focused, so we provide delicious free lunches for everyone working from our hubs. It’s one less thing for you to worry about during a productive workday - Public Holidays Policy: Gismart observes public holidays based on the Ukrainian or Polish holiday calendars. Employees working in other locations are entitled to 12 public holidays per year - 100% Sick Leave Compensation - Mental and Physical Health: To help you stay happy and healthy, Gismart will partially cover your medical insurance, sports activities, therapy costs - Personal Equipment Policy: Of course, we’ll provide you with all the equipment you need or cover the maintenance cost for your own tools - Personal Learning and Development: We love to see you learn and grow, so Gismart will cover 70% of your professional development courses. We’ll also pay for 100% of corporate English courses - Time-Off Policy: Every employee gets 18 working days of paid vacation and 3 personal days per year, with an extra day added for each year at Gismart - Corporate Events: We are remote-first, but we love meeting up in person. Whenever possible, we organize corporate events and team-building activities across all Gismart hubs

Location: Boston, MA Workplace: OnSite At WHOOP, we’re on a mission to unlock human performance and healthspan. WHOOP empowers members to perform at a higher level through a deeper understanding of their bodies, behaviors, and daily lives.   WHOOP Labs is the on-site research facility for product development and innovation at WHOOP. We conduct human-centered hardware and algorithm research to create best-in-class product experiences that work for all members.   WHOOP is hiring a Researcher II to support research planning and execution on weekends, supporting critical data collection windows for participant diversity and expanded access. This role will cover a broad range of research studies for algorithm training, hardware validation, and design testing. While your home base will be WHOOP’s on-site product research facility, WHOOP Labs, studies will include field collections across the metro Boston area to widen access for diverse communities. Your efforts will support the organization as we continue to develop a best-in-class experience and lead the wearables industry.   *This role is fully onsite at our Boston, MA office and follows a 4x10 schedule, with four 10-hour workdays each week, Friday through Monday, and three days off Tuesday through Thursday.   RESPONSIBILITIES - Execute testing protocols across multiple concurrent studies, owning research execution on weekends and collaborating with other researchers on Friday and Monday to ensure consistent protocol administration across all days and shifts. - Own research documentation for weekend hours, collaborating with other researchers on Friday and Monday to ensure effective handoffs and information transfer across shifts. - Provide coaching and guidance to participants during exercise protocols, balancing data integrity, research best practices, and participant experience - Create a supportive and welcoming environment for participants engaging in a range of research tasks, from exercises to device interactions - Manage the use, troubleshooting, and upkeep of sensitive data collection equipment and prototype devices - Develop strong working knowledge of WHOOP’s research platform tooling suite, with the ability to troubleshoot issues in real time—including during active data collections—and problem-solve on the fly - Develop junior researchers by providing technical coaching, delegation, constructive feedback, and growth opportunities - Own daily lab management tasks required for data collections to be successful, such as laundry, equipment cleaning, material organization, and overall lab readiness - Serve as an ambassador for WHOOP Labs and the WHOOP brand   QUALIFICATIONS - Bachelor’s Degree in human physiology, biomedical engineering, psychology, HCI, or similar - Professional experience in research & development, human subjects research, or a related field, including 2+ years of experience conducting human subjects research - Strong technological background and working knowledge of data management systems including the Google Suite - Familiarity with research platform tools and hardware testing environments preferred - Strong interpersonal communication skills with a savvy for working as part of a highly collaborative, fast-paced team - Ability to manage multiple priorities and adapt quickly in dynamic research settings - Prior experience in customer service or other public-facing roles a plus - Strong written, verbal, and presentation skills, with confidence giving and receiving feedback across disciplines   Interested in the role, but don’t meet every qualification? We encourage you to still apply! At WHOOP, we believe there is much more to a candidate than what is written on paper, and we value character as much as experience. As we continue to build a diverse and inclusive environment, we encourage anyone who is interested in this role to apply. WHOOP is an Equal Opportunity Employer and participates in E-verify to determine employment eligibility. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability. The WHOOP compensation philosophy is designed to attract, motivate, and retain exceptional talent by offering competitive base salaries, meaningful equity, and consistent pay practices that reflect our mission and core values. At WHOOP, we view total compensation as the combination of base salary, equity, and benefits, with equity serving as a key differentiator that aligns our employees with the long-term success of the company and allows every member of our corporate team to own part of WHOOP and share in the company’s long-term growth and success. The U.S. base salary range for this full-time position is $75,000 - $95,000. Salary ranges are determined by role, level, and location. Within each range, individual pay is based on factors such as job-related skills, experience, performance, and relevant education or training. In addition to the base salary, the successful candidate will also receive benefits and a generous equity package. These ranges may be modified in the future to reflect evolving market conditions and organizational needs. While most offers will typically fall toward the starting point of the range, total compensation will depend on the candidate’s specific qualifications, expertise, and alignment with the role’s requirements.

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: Berlin Office; Germany Workplace: Remote The AI orchestration of your wildest imagination. n8n is the open workflow orchestration platform built for the new era of AI. We give technical teams the freedom of code with the speed of no-code, so they can automate faster, smarter, and without limits. Backed by a fiercely inventive community and 500+ builder-approved integrations, we’re changing the way people bring systems together and scale ideas for impact. Since our founding in 2019, we’ve grown into a diverse team of over 260 - working across Europe and the US, connected by a shared builder spirit and with our centre of gravity in Berlin. Along the way, we’ve: - Cultivated a community of more than 650,000 active developers and builders - Earned 190K+ GitHub stars, making us one of the world’s Top 40 most popular projects - Backed by top investors, from Sequoia’s first German seed to our SAP's recent strategic investment - bringing us to a $5.2bn valuation That’s the company we’ve built. Now we’d love to see what you can build. If you’re applying, try n8n out - whether you’re technical or not - and share a screenshot of your first workflow with us. The easiest place to start is here: app.n8n.cloud/register http://app.n8n.cloud/register. We’re in a defining moment of an incredible journey. Come and build with us. ABOUT THE ROLE Your goal will be to build DACH into n8n's most predictable Enterprise sales region - developing a team of high-performing Enterprise AEs, instilling forecast and pipeline discipline, and creating a repeatable operating model that wins complex, multi-stakeholder deals To make that happen, you'll be hands-on in coaching, deal inspection, and team development day-to-day, while staying close enough to strategic deals and customer executives to raise the bar on how we qualify, forecast, and win. What you’ll be doing   DEVELOPING A HIGH-PERFORMING, PREDICTABLE DACH TEAM - Coach and develop a team of Enterprise AEs through structured 1:1s, field coaching, and deal reviews – raising both the floor and the ceiling on individual performance - Build a rigorous forecasting and pipeline management cadence that makes DACH's numbers predictable quarter over quarter, not dependent on late-quarter heroics - Create a repeatable operating model – clear playbooks, MEDDIC/MEDDPICC-based deal inspection, and coaching rhythms – DACH's execution shouldn’t rely on you personally driving every strategic deal - Hire, onboard, and scale the team over time, establishing career paths and succession plans as the region grows SETTING THE STRATEGY FOR THE DACH TERRITORY - Prioritize and run the DACH Enterprise territory with focus – balancing new logo pursuits with expansion plays where community signals are strong - Set the strategy for the team's most complex enterprise cycles, from discovery to close, staying close enough to coach without taking the pen - Elevate sales methodology adoption (MEDDIC/MEDDPICC), ensuring meticulous qualification, mutual action plans, and disciplined inspection of technical + business wins BUILDING A STRATEGIC, MULTI-THREADED SELLING MOTION - Build a strategic selling culture that shifts the team from “running opportunities” to multi-threaded, value-led enterprise execution - Orchestrate executive engagement across DACH accounts – aligning economic buyers, champions, and technical evaluators to keep momentum and unblock deals - Run high-quality deal reviews and QBRs that sharpen strategy, elevate coaching moments, and improve win rates, cycle time, and forecast accuracy   PARTNERING ACROSS THE BUSINESS - Collaborate cross-functionally (Solutions Engineering, Customer Success, Marketing, RevOps, Product) to refine messaging for technical buyers, strengthen the enterprise playbook, and remove friction in the sales process REQUIREMENTS MUST HAVES - 🏆 Enterprise sales leadership: 5+ years in frontline sales management, leading ICs through complex, multi-threaded enterprise deals - 🔎 MEDDIC/MEDDPICC mastery: Deep, practical command of MEDDIC/MEDDPICC and a track record coaching teams to adopt it with real inspection - 📈 Forecast & pipeline rigor: Track record running a disciplined forecasting and pipeline management cadence that makes revenue predictable, not reactive - 🧠 Strategic deal management: You’re fluent in qualification, mutual action plans, champion building, and executive alignment in longer-cycle deals - 🎙️ Executive presence: You confidently engage senior stakeholders, run tight meetings, and set a high bar for clarity, urgency, and outcomes - 🧑‍🏫 Coaching & talent development: You level up AEs through structured coaching, field observation, and actionable feedback - 🧩 Multi-stakeholder navigation: You’re skilled at aligning technical and economic buyers, de-escalating conflict, and maintaining deal momentum - 🇩🇪 DE location: You’re based in Germany and happy being on-site with customers - 🔧 Technical-buyer credibility: Experience selling into technical stakeholders and navigating evaluation-heavy sales motions NICE-TO-HAVES - 🖥️ Open-source / PLG experience: You understand how community and bottoms-up adoption influence enterprise outcomes and how to partner with that motion - 🌉 Developer / infra SaaS background: Experience in DevOps, SecOps, IT Ops, data, infrastructure, or adjacent categories - 💡 Scrappy startup mindset: You’ve scaled in environments where playbooks are evolving and you enjoy building structure without slowing teams down - 📊 Operational excellence: Strong instincts for clean forecasting, pipeline hygiene, and turning data into coaching and better execution n8n is an equal opportunity employer and does not discriminate on the basis of race, religion, colour, national origin, gender, sexual orientation, gender identity, age, marital status, veteran status, or disability status. We can sponsor visas to Germany; for any other country, you need to have existing right to work. Our company language is English. You care about diversity and inclusion? We do too! Check out our Diversity, Inclusion and Belonging initiatives at n8n https://www.notion.so/Diversity-inclusion-and-belonging-n8n-c1bec2fff536422d868b1a438d990e35?pvs=21 (https://www.notion.so/n8n/Diversity-inclusion-and-belonging-n8n-c1bec2fff536422d868b1a438d990e35). Location disclaimer: If you see multiple job postings for the same role, it is most likely because we're hiring remotely for this role and posting in different locations to make sure every potential candidate can see the role. Please apply to the location you're the most likely to work from in the future. BENEFITS - Competitive compensation 💸 – We offer fair and attractive pay. - Ownership 💪 – Our core value is to “empower others,” and we mean it—you’ll get a slice of n8n with equity. - Work/life balance 🏖️ – We work hard but ensure you have time to recharge: - Europe: 30 days of vacation, plus public holidays wherever you are. - US: 20 vacation days, 8 sick days, plus public holidays wherever you are. - Health & wellness 🩺 – - Europe: We provide benefits according to local country norms.* - US: Multiple low-premium, low-deductible medical plans with coverage for individuals and families—plus a no-cost premium HDHP option with a pre-seeded HSA—along with dental and vision coverage. - Future planning 💰 – - Europe: We provide pension contributions according to local country norms.* - US: 401(k) retirement plan with a 4% employer match. - Financial security 🛡️ – - Europe: We provide benefits according to local country norms.* - US: Company-paid short-term and long-term disability insurance, plus life insurance to support you and your loved ones. - Career growth 📈 – We hire rising stars who grow with us! You’ll get €1K (or equivalent) per year to spend on courses, books, events, or coaching to level up your skills. - A passionate team 🤩 – We love our product, and we prove it with regular hackathons where we see who can build the coolest thing with it! - Remote-first 🌏 – Our team works remotely across Europe, with regular off-sites for team bonding. Some roles, like sales in the US, are hybrid—please check the job description. - Giving back 🤝 – We're big fans of open source, and you'll get $100 per month to support projects you care about. - Transparency 🙏 – We all know what everyone’s working on, how the company is doing—the whole shebang. *Country and/or State specific details provided in your employment agreement.

Location: Munich, Germany About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As an Enterprise Account Executive at Anthropic, you'll join the foundational team at the forefront of introducing our cutting-edge AI productivity SaaS solution to large enterprise organizations across CEE. You'll drive the adoption of safe, frontier AI by securing strategic deals with major corporations, technology companies, and research institutions. You'll leverage your consultative sales expertise in the enterprise sector to propel revenue growth while becoming a trusted partner to enterprise stakeholders, helping them embed and deploy AI while uncovering its full range of capabilities across business operations, research, and administration. In collaboration with GTM, Product, and Marketing teams, you'll continuously refine our value proposition, sales methodology, and market positioning to resonate with enterprise decision-makers in the CEE market. Responsibilities: Win new business and drive revenue for Anthropic within the enterprise sector across CEE. Navigate complex enterprise organizations to reach key decision-makers, educate them about our services, and help them succeed with Anthropic. You'll own the full sales cycle, from first outbound to close Design and execute innovative sales strategies tailored to enterprise procurement cycles and budgeting processes to meet and exceed revenue quotas. Analyze enterprise market landscapes, trends, and dynamics to translate high-level plans into targeted sales activities and campaigns Spearhead market expansion by identifying new use cases within enterprise departments, innovation centers, and operational offices. Collaborate cross-functionally to differentiate our offerings for enterprise applications Navigate complex enterprise stakeholder ecosystems including executives, administrators, IT departments, and procurement offices to build consensus across CEE business culture and practices Inform product roadmaps and features by gathering feedback from enterprise users and conveying market needs from the CEE enterprise landscape. Provide insights that strengthen our value proposition for enterprise customers Continuously refine the enterprise sales methodology by incorporating learnings into playbooks, templates, and best practices. Identify process improvements that optimize sales productivity and consistency You may be a good fit if you have: 7+ years of B2B sales experience in enterprise technology, preferably pharmaceuticals or life sciences A track record of managing complex sales cycles within large enterprise organizations and securing strategic deals by understanding both technical requirements and business use cases Demonstrated ability to navigate enterprise bureaucracies and procurement processes, building consensus among diverse stakeholders including executives, administrators, and IT departments Extensive experience negotiating complex agreements within enterprise procurement frameworks and policies Proven experience exceeding revenue targets in the enterprise sector by effectively managing an evolving pipeline and sales process Excellent communication skills and the ability to present confidently to various enterprise audiences, from technical teams and business analysts to senior executives Deep understanding of enterprise buying cycles, decision-making processes, and key pain points, particularly within the CEE market A strategic, analytical approach to assessing the enterprise market combined with creative, tactical execution to capture opportunities A passion for and/or experience with advanced AI systems and their applications in enterprise environments. You feel strongly about ensuring frontier AI systems are developed safely and ethically for business use What We Offer: Competitive base salary and commission structure Equity participation in Anthropic's growth Comprehensive benefits package Opportunity to shape the AI industry in CEE Professional development and career growth opportunities Location: Munich, Germany (hybrid working available) The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: €265.000 — €310.000 EUR Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

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: Paris; Amsterdam; Munich; London; Berlin Workplace: Remote ABOUT MISTRAL Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. THE TEAM Mistral is building a sovereign AI cloud for Europe. Our customers in finance, healthcare, and the public sector run frontier models on European-jurisdiction infrastructure, and the Cloud Platform team builds the systems that make that possible — compute orchestration, Kubernetes, bare metal, storage, networking, and the datacenter fleet that runs it all. We run it all on our own metal, our own network, our own datacenters — which means when something breaks, the fix is ours to write. European Compute Units let enterprises commit to multi-year capacity on that infrastructure, and we are scaling toward a gigawatt of compute across Europe by 2030. You will design and ship the layer every sovereign AI deployment depends on and shape the team building it. THE ROLE This is a people-leadership role from day one. You will manage the team — hiring, coaching, performance, growth paths, honest feedback — while staying close to the code: roughly half your time in architecture decisions and the hardest technical problems the team faces, the other half leading your squad. If you are looking for a senior IC role, this is not it. You will lead the team building our serverless containers product: the way developers run AI apps, MCP servers, APIs, and managed workers on our cloud without thinking about servers. Push a container, get an endpoint, scale from zero to thousands of instances and back down — across CPU and GPU. On a hyperscaler, the serverless layer is a product someone else built. Here you own it end to end: the scheduler that decides where a container lands, the routing path a request takes, the machinery that turns a scaled-to-zero service into a warm instance before a customer notices. All of it runs on metal, network, and datacenters we own. That tension is the product: scale-to-zero economics with cold starts in milliseconds, autoscaling that absorbs a launch spike without a config change, GPUs scheduled onto containers the way other platforms schedule CPU. The customers betting on this layer are the developers building the next generation of AI software on European infrastructure. WHAT YOU WILL DO - Own the container platform end to end: image delivery, placement, request routing, scale-up, scale-to-zero — across CPU and GPU. - Make cold starts a solved problem: snapshotting, prewarming, image-layer caching, whatever it takes for scale-from-zero to feel instant. - Treat AI workloads as the normal case: GPU-backed containers, streaming responses, long-lived connections, MCP servers that cost almost nothing while idle. - Write Go alongside your team and own the architecture and the hardest implementation decisions. - Grow the engineers, not just the software — set the standard for ownership and coach people past their comfort zone. - Own people management for the team: hiring, performance, growth paths, and honest feedback. - Partner with Product Managers to turn platform decisions into a product developers want to deploy on. WHAT WE'RE LOOKING FOR - 3+ years of real people leadership. You have managed engineers — hired, coached, given honest feedback, and grown them. Hands-on contribution matters here, but this role is judged on the team you build and lead, not just the code you write. - You have shipped production systems in Go. Not dabbled. Shipped. - You have built container or workload platforms — orchestration, scheduling, isolation, request routing — not just deployed onto someone else's serverless platform. - Deep Linux: namespaces, cgroups, image layers, page cache — comfortable well below the application layer. - Multi-tenancy instincts: density, isolation, and fairness when hundreds of customers share one fleet. - Significant experience building complex backend or infrastructure systems. - You have partnered with product, design, and business teams to ship software that reached real users. - A low-ego, team-first mindset. We care less about your exact domain and more about whether you are the kind of technical force other engineers want to work alongside. WHAT WE OFFER We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page https://app.notion.com/p/mistralai/Benefits-at-Mistral-36e6ba59a7fe836b93dd01737fcc27ef?source=copy_link. PRIVACY POLICY Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy https://legal.mistral.ai/terms/applicant-privacy-policy.

Responsibilities: — Own the MSP channel marketing motion end-to-end: partner onboarding content, lifecycle email programs, enablement webinar series, and support the annual event calendar (e.g., MSP Summit, IT Nation Connect). — Develop the annual Channel Marketing Plan: event selection, budget, campaign strategy, and executive approval process, in partnership with the Marketing and Sales leadership. — Serve as the marketing primary point of contact for Channel Sales (MSP, reseller, VAR) — running the biweekly Channel Marketing meeting, managing the event intake process, and building/evolving the deliverables (templates, briefs, self-serve assets) that empower Sales to execute quickly and independently. — Own reporting on program performance: pipeline influenced, partner engagement, event ROI, and progress against the $5M combined reseller/MSP revenue target, presented to marketing and sales leadership. — Extend proven partner playbooks — onboarding sequences, enablement content, partner toolkits, prioritizing by revenue contribution and need (starting with enabling active partners). — Build and drive a proactive, always-on partner demand generation strategy to drive net-new target partner interest (e.g., partners in uncovered territories/regions) with a coherent plan tied to pipeline and ARR targets. — Manage the channel marketing budget across sponsorships, campaigns, and partner enablement programs, and make prioritization trade-offs as new event and partner requests come in. — Partner with Marketing Operations, Comms, and Product Marketing to keep partner-facing content, campaigns, and the partner portal current and aligned to brand and product roadmap. — Wherever possible, focus on public facing web documents that are visible globally by individuals and AI agents. — Assist with the administration of the Bitwarden partner portal and ensure content is up-to-date, accessible, and aligned with go-to-market priorities. Requirements: — 7+ years of B2B channel, partner, or field marketing experience — ideally including work with MSPs, resellers, or VARs in a SaaS or technology company. — Proven ability to own a marketing program end-to-end: strategy, budget, execution, and reporting, without heavy hands-on direction. — Experience planning and executing in-person or virtual partner events, from sponsorship negotiation through post-event lead follow-up. — Experience building or running partner lifecycle email programs (onboarding, engagement, re-engagement) — comfort partnering with marketing ops/automation owners to execute them. — A track record of turning a reactive, request-driven function into a proactive, planned one — you build the calendar instead of just reacting to what lands in your inbox. — Strong cross-functional collaboration skills — this role sits at the intersection of Growth Marketing, Channel Sales, and Marketing Operations, and will need trust from all three. — Comfort with ambiguity and prioritization — you'll be handed more inbound requests (events, campaigns, partner asks) than one person can execute, and part of the job is deciding what not to do. — Collaborative and adaptable mindset. — Openness and authenticity combined with excellent communication skills. — Excitement and enthusiasm for open source and for better internet security. — Excellent problem-solving skills – you might not know all the answers, but you know how to find and communicate the solution. Interview Process: — Meeting with our Recruiting Manager. — Interview with the Head of Growth Marketing and Operations. — Interview(s) with Channel Sales stakeholders (e.g., Channel Sales Manager, Channel Sales AE). — Interview(s) with Growth Marketing team members (e.g., Demand Generation, Product Marketing). — Interview with the Chief Customer Officer. — Reference calls.

Задачи: — Ведение федерального государственного контрактования, включая работу с основными контрактами, субподрядами, требованиями flow-down и обязательствами по соблюдению программ. — Самостоятельное составление и согласование коммерческих договоров с клиентами, партнерами, поставщиками и медицинскими провайдерами, включая SaaS, лицензирование ПО, клинические услуги, профессиональные услуги, бизнес-ассоциаты, реселлеры и соглашения по защите данных. — Консультирование бизнеса по структуре контрактов, распределению рисков, требованиям закупок, нормативным аспектам здравоохранения, вопросам конфиденциальности и операционным обязательствам. — Поддержка в подготовке ответов на запросы информации (RFI) и запросы предложений (RFP), включая юридический и комплаенс-обзор. — Участие в регуляторных и комплаенс-проектах, особенно на пересечении коммерческих, медицинских, приватных и государственных требований. — Сопровождение трудовых вопросов совместно с HR и руководителем юридического отдела, включая трудовые и соглашения о расторжении, политики и повседневные вопросы. — Помощь в управлении спорами и судебными процессами, включая организацию хранения документов, взаимодействие с внутренними и внешними сторонами, поддержку в процессе раскрытия информации и оценку рисков. — Взаимодействие с кросс-функциональными командами для согласования нестандартных условий, участия в обзоре сделок и контроля обязательств. — Улучшение контрактных шаблонов, методических материалов, процессов и инструментов для повышения эффективности работы команды. — Изучение платформы Amwell, дорожной карты продуктов и модели предоставления услуг для обеспечения практических рекомендаций. Требования: — Диплом юриста (J.D.) из аккредитованной ABA школы и действующее членство в коллегии адвокатов США. — Более 15 лет релевантного юридического опыта, включая значительную работу с коммерческими контрактами. — Опыт работы в юридическом отделе технологической, медицинской, цифровой или SaaS-компании приветствуется. — Глубокие знания федерального, штатного или местного государственного контрактования, включая требования закупок, flow-down положения, субподряды, обязательства по соблюдению, государственные RFP и поддержку регулируемых программ. — Опыт составления и согласования различных договоров (технологии, SaaS, лицензирование ПО, услуги медицинских провайдеров, бизнес-ассоциаты, защита данных, профессиональные услуги). — Практическое суждение, умение выделять главное, ясно объяснять сложные вопросы и предлагать разумные решения. — Умение работать в условиях неопределенности, оценивать риски и принимать решения без полной информации. — Организованность, внимание к деталям и способность отслеживать сложные требования контрактов и комплаенса. — Четкие и дружелюбные навыки письменного и устного общения. — Готовность к сотрудничеству и работе в межфункциональных командах. Преимущества: — Наличие или возможность получения T1 public trust clearance. — Знакомство с технологиями здравоохранения, цифровым здравоохранением, телемедициной, страховыми планами, провайдерами, вопросами конфиденциальности и безопасности данных. Условия: — Полная занятость. — Удаленная работа. — Годовой оклад в диапазоне $170,190 - $208,010, окончательное предложение зависит от опыта, навыков и других факторов. — Возможность годового бонуса, долгосрочных и краткосрочных переменных выплат. — Программа пенсионных накоплений 401K с матчингом. — Конкурентные планы медицинского, стоматологического и офтальмологического страхования. — Оплачиваемый отпуск по уходу за ребенком. — Программа покупки акций сотрудниками. — Бесплатный доступ к телемедицинским сервисам Amwell и другим программам поддержки здоровья. — Гибкий график, включая летние пятницы и дни психического здоровья. Контакт для отклика отсутствует в тексте.

Location: Munich, Germany About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As an Enterprise Account Executive at Anthropic, you'll join the foundational team at the forefront of introducing our cutting-edge AI productivity SaaS solution to large enterprise organizations across DACH. You'll drive the adoption of safe, frontier AI by securing strategic deals with major corporations, technology companies, and research institutions. You'll leverage your consultative sales expertise in the enterprise sector to propel revenue growth while becoming a trusted partner to enterprise stakeholders, helping them embed and deploy AI while uncovering its full range of capabilities across business operations, research, and administration. In collaboration with GTM, Product, and Marketing teams, you'll continuously refine our value proposition, sales methodology, and market positioning to resonate with enterprise decision-makers in the German market. Responsibilities: Win new business and drive revenue for Anthropic within the enterprise sector across DACH. Navigate complex enterprise organizations to reach key decision-makers, educate them about our services, and help them succeed with Anthropic. You'll own the full sales cycle, from first outbound to close Design and execute innovative sales strategies tailored to enterprise procurement cycles and budgeting processes to meet and exceed revenue quotas. Analyze enterprise market landscapes, trends, and dynamics to translate high-level plans into targeted sales activities and campaigns Spearhead market expansion by identifying new use cases within enterprise departments, innovation centers, and operational offices. Collaborate cross-functionally to differentiate our offerings for enterprise applications Navigate complex enterprise stakeholder ecosystems including executives, administrators, IT departments, and procurement offices to build consensus across DACH business culture and practices Inform product roadmaps and features by gathering feedback from enterprise users and conveying market needs from the German enterprise landscape. Provide insights that strengthen our value proposition for enterprise customers Continuously refine the enterprise sales methodology by incorporating learnings into playbooks, templates, and best practices. Identify process improvements that optimize sales productivity and consistency You may be a good fit if you have: Native German speaker with excellent written and verbal communication skills in German and English 7+ years of B2B sales experience in enterprise technology, preferably in SaaS or emerging technologies Specialised sales industries experience: Energy & Utilities A track record of managing complex sales cycles within large enterprise organizations and securing strategic deals by understanding both technical requirements and business use cases Demonstrated ability to navigate enterprise bureaucracies and procurement processes, building consensus among diverse stakeholders including executives, administrators, and IT departments Extensive experience negotiating complex agreements within enterprise procurement frameworks and policies Proven experience exceeding revenue targets in the enterprise sector by effectively managing an evolving pipeline and sales process Excellent communication skills and the ability to present confidently to various enterprise audiences, from technical teams and business analysts to senior executives Deep understanding of enterprise buying cycles, decision-making processes, and key pain points, particularly within the German market A strategic, analytical approach to assessing the enterprise market combined with creative, tactical execution to capture opportunities A passion for and/or experience with advanced AI systems and their applications in enterprise environments. You feel strongly about ensuring frontier AI systems are developed safely and ethically for business use What We Offer: Competitive base salary and commission structure Equity participation in Anthropic's growth Comprehensive benefits package Opportunity to shape the AI industry in DACH and EMEA Professional development and career growth opportunities Location: Munich, Germany (hybrid working available) Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: Limassol; Belgrade Workplace: onsite About Unlimit Unlimit is the global financial infrastructure for the borderless agentic economy. Designed to bridge the gap between fragmented local markets and the future of autonomous commerce, Unlimit provides the programmable operating layer for the world’s most ambitious businesses. Through an integrated technology stack, the platform unifies global payment acceptance, programmable financial accounts, and digital asset rails into a singular financial layer. By mapping hyper-local payment ecosystems directly into its architecture, Unlimit enables businesses to move value and settle transactions instantly across continents. Built on decades of hard-won regulatory depth and an extensive global license portfolio, the platform provides direct access to a massive global infrastructure. With major hubs in London, San Francisco, Singapore, São Paulo, and Mexico City, Unlimit is building the infrastructure that makes global expansion a matter of code, not geography. About the role: We are looking for a senior engineer to become the technical lead of our card processing platform. You will own the SmartVista ecosystem end to end (FrontEnd and BackOffice), set the standards for how processing is built, changed and operated, and lead the work of finding and closing gaps in our processes, configuration and controls. This is not a pure support or configuration role. We expect you to replace manual work with automation and to put AI to practical use in processing operations: anomaly detection, intelligent alerting, automated root-cause analysis and AI-assisted analysis of scheme specifications and transaction data. The role combines card processing expertise + technical leadership + engineering (backend, scripting, integrations) + automation and AI adoption. What you will do: 1. Technical leadership and platform ownership Own the end-to-end architecture of the processing ecosystem (SmartVista FrontEnd and BackOffice, interfaces, HSM, scheme connectivity) and make architecture and technology-stack decisions. Act as the technical lead and senior escalation point for processing engineers; set engineering standards, review solutions. Lead major incidents, coordinate the response with internal teams, the vendor and card schemes, and drive post-incident reviews to permanent fixes. Manage the relationship with the SmartVista vendor on releases, patches, defects and change requests. 2. Process ownership and gap remediation Map the current processing processes (authorisation, clearing, settlement, disputes, reconciliation, reporting, release and change management, monitoring and on-call) and identify gaps, single points of failure and manual workarounds. Build and run a remediation plan: define owners, deadlines and measurable outcomes, and follow through to closure. Introduce and maintain operational standards: runbooks, release and change procedures, incident and problem management, SLAs and KPIs (e.g. availability, approval rate, incident resolution time). Make sure scheme mandates and regulatory changes are tracked, assessed and implemented on time, and that the evidence of compliance is documented. 3. Processing development and scheme compliance Deliver the technical implementation of new card products and services (acquiring and issuing) for Visa, Mastercard, UnionPay, American Express and other schemes. Translate scheme mandates and specifications into technical solutions, and lead certification projects with the schemes. Configure and develop SmartVista FrontEnd and BackOffice products, services and business rules. Prepare technical requirements for system upgrades; test and install releases and patches with minimal downtime. Diagnose complex issues across authorisation, clearing and settlement flows and drive them to root cause. Set up and maintain payment system emulators and test environments; take part in go-live and pilot activities. Maintain clear technical documentation of the platform and implementation procedures. 4. Monitoring and observability: design, development and implementation Design and build an end-to-end monitoring framework for the processing platform, covering infrastructure, applications, interfaces and business metrics. Develop and implement real-time monitoring of: - authorisation flows: approval and decline rates by scheme, BIN, issuer country, merchant, MCC and response code. - response times, timeouts and stand-in processing. - scheme, issuer and HSM connectivity and host availability. - transaction volumes and abnormal spikes or drops. Develop and implement monitoring of back-office processes: - clearing file generation, submission and acknowledgement (Visa, Mastercard and other schemes). - incoming scheme files and reports, settlement positions and reconciliation breaks. - end-of-day and batch jobs, interchange and fee calculation, chargeback and dispute deadlines. Monitor scheme compliance indicators (e.g. decline-code usage, data-integrity edits, excessive retries, fraud and dispute ratios) to catch issues before they become scheme non-compliance or fines. Define thresholds, alerting rules and escalation paths; integrate alerts with on-call, incident management and messaging tools. Build operational dashboards for engineering, operations and management, and define the related KPIs and SLAs. Develop health checks, synthetic test transactions and log-based monitoring for SmartVista components. Continuously tune monitoring to reduce false alerts, and turn incident findings into new checks and controls. 5. Automation and AI Identify manual and repetitive processes and automate them, including: - reconciliation and settlement. - scheme file exchange and report submission. - testing, regression and release management. - monitoring and alerting. Build CI/CD pipelines and automated deployment for processing components and configuration. Design and deliver AI-driven solutions for processing operations, for example: - anomaly detection on transaction flows, decline patterns and fraud signals. - intelligent alerting that reduces noise and escalates what matters. - automated root-cause analysis of declines and incidents - AI assistants or agents that analyse scheme specifications, mandates and authorisation messages and flag deviations. Introduce test automation and regression frameworks for scheme messages and processing flows. Promote the safe use of AI tools across the team, with appropriate controls for data security, PCI DSS and human oversight of changes to production. What you bring: 6+ years of hands-on experience in card processing, covering the full transaction lifecycle: authorisation, clearing, settlement, chargebacks and reconciliation. At least 2 years in a senior, lead or architect role, with a track record of owning a processing platform and leading engineers, directly or as a technical lead. Strong practical experience with SmartVista (FrontEnd and/or BackOffice); deep experience with acomparable platform (e.g. Way4, TranzWare) may be considered. Proven experience of improving processes: finding operational gaps, designing controls and delivering a remediation plan to completion. Certification experience with Visa and Mastercard and the ability to read and apply scheme specifications and rules (ISO 8583, Visa Base I/II, Mastercard IPM/CIS). Hands-on automation skills: Python, SQL/PL/SQL, Bash; experience with CI/CD tools (e.g. GitLab CI, Jenkins), test automation and API testing (e.g. Postman). Practical experience applying AI or ML in production work, such as anomaly detection, LLM-based tools or agents, or AI-assisted analysis and coding, and a clear view of their limits and risks. Working knowledge of Oracle DB, WebLogic, Linux, REST/SOAP web services and HTTP. Experience with scheme tools: Visa Edit Package, VCX, Mastercard File Express (MFE) and scheme test tools and emulators (e.g. Mastercard MAX, Visa test systems). Good understanding of e-commerce and digital payments: EMV 3-D Secure, tokenisation (VTS/MDES), Apple Pay / Google Pay, recurring payments, AVS. Knowledge of card technologies and security: EMV, contactless, HSM (Thales), key management, PCI DSS. Experience with release and change management in a 24/7 production environment. Fluent English (B2+) for daily communication with card schemes, vendors and international teams. What we offer: A key role with real ownership of a business-critical platform and visible impact on approval rates, stability and time to market. The mandate and support to modernise processing with automation and AI. Competitive salary and performance-based rewards. Paid vacation, sick leave and public holidays. Flexible working hours and modern equipment. An international team of payments professionals in a fast-growing fintech. Join Unlimit Team now!   Unlimit is an equal opportunity employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We welcome applications from all members of society irrespective of age, sex, disability, sexual orientation, race, religion or belief.   We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Location: Georgia; Armenia; Poland; Kazakhstan; Uzbekistan; European Union Workplace: Remote 🌍 Remote | UTC+8 | Core collaboration hours: 12:00–6:00 PM Manila Time Salmon is a technology-driven financial company building a banking and lending platform across Southeast Asia, starting in the Philippines. We combine global fintech expertise with deep local market knowledge to make financial services simple, accessible, and useful for millions of people across the region. 11M+ app downloads. 2M+ monthly active users. 10000+ partner stores. US$400M+ raised from top-tier investors. Manila-based, globally distributed, and hybrid-first — our team spans 45+ countries. If you want to solve complex problems at scale and impact how millions of people access and manage money, come build with us. Southeast Asia's fintech moment starts here. About the role: You'll own how Credit Line scales next, leading its move into the Philippine middle class with better customers, higher limits, and healthier repayment. What you'll do: - Own the full Credit Line funnel — from awareness with marketing through acquisition, activation, and retention inside the product — with no dedicated engineering squad, so you're the connective layer holding marketing, acquisition, product, risk, and business together. - Work closely with marketing, product, acquisition, design, risk and origination, affiliates, and web/SEO, and be the person the team comes to when they need to align on growth. - Report to the Head of Growth and own the Credit Line acquisition budget — no direct reports, but real leverage over numbers that matter commercially. What you'll own: - Define and drive Credit Line's growth strategy end-to-end with the business team — what to test, scale, or kill. - Own the acquisition budget and decide where it goes. - Lead the move into the Philippine middle class — define who that customer is, where to reach them, and rebuild the acquisition mix around them. - Turn a real read on what customers need, fear, and compare us against into experiments worth running — hands-on when the bet calls for it, from testing a new channel to shipping the landing page yourself. - Run experiments across paid channels, landing pages, onboarding, activation, and retention with acquisition and product, tracking CAC, approval, activation, first transaction, limit utilization, spend per active, retention, reactivation, and LTV against cost of risk to find where the real leverage is. - Build a clean experiment-tracking system so learnings compound across quarters instead of getting lost. What makes you a strong fit: - 5+ years in growth, performance, or product marketing. - A track record of self-generated experiments that actually shipped and moved metrics. - Comfortable with product metrics and the tools behind them: CAC, LTV, activation, cohort retention in GA and AppsFlyer, Tableau, plus a working understanding of Meta, TikTok, and Google Ads Manager. - Hands-on with both qualitative and quantitative research — user interviews, large studies, segmentation, market signals. - Uses AI daily for prototypes, creative variants, and analysis, and knows when to override it rather than trust it blindly. - Strong project management and fluent English. What we offer: Ownership and flexibility - Fully remote work with core collaboration hours from 12:00 to 6:00 PM Manila time (UTC+8) - Company-provided tools and equipment Health and time off - Medical insurance support for you and your family through co-funding or reimbursement, depending on your location and subject to policy limits - Access to an internal mental health support specialist - 22 vacation days, Philippine public holidays, and 15 sick days Growth and team experience - Opportunities to learn and share your expertise through internal expert meetups, external conferences, speaking opportunities, and industry publications - Company-sponsored trips to Manila to meet and work with your team in person - High-performing teams can earn a dedicated beach house week in Southeast Asia

Location: Egypt (Remote) Workplace: Remote ABOUT THE OPPORTUNITY We are looking for experienced Government professionals to support a cutting-edge AI benchmarking project focused on Egyptian public sector environments. As a Subject Matter Expert, you will create and review realistic, high-quality scenarios that reflect operational, administrative, compliance, public safety, social service, and community engagement challenges across government institutions. Your expertise will help ensure AI systems understand and respond accurately within highly regulated and citizen-focused environments. WHAT YOU’LL DELIVER - Design realistic government scenarios in Arabic or English grounded in Egyptian public sector contexts (e.g., administrative operations, social services, compliance reviews, public safety coordination, community programs, citizen service delivery) - Adapt structured evaluation rubrics for operational problem-solving, policy interpretation, case management, and decision-making tasks - Review AI and human-generated responses for factual accuracy, procedural compliance, cultural appropriateness, and operational realism - Contribute to “gold standard” solutions reflecting public sector and government best practices QUALIFICATIONS - Native Arabic with strong professional English proficiency - 5+ years of professional experience in government, public administration, social services, public safety, compliance, or community programs - Background in one or more relevant roles: Administrative Services Management, Child/Family/School Social Work, Compliance & Regulatory Affairs, Police or Public Safety Supervision, Recreation & Community Services, or related government functions - Strong understanding of public sector workflows, operational procedures, regulatory requirements, and Egyptian government environments WHY COLLABORATE WITH LILT? - Your schedule, your rules. As an independent contractor, work when you want, as much or as little as you want. No fixed hours, no check-ins, no micromanaging. - Get paid quickly and fairly. We respect your time and your expertise. Competitive rates, prompt payments, no chasing invoices. - Work on projects that actually matter. Contribute to cutting-edge AI and language technology that is shaping how humans and machines communicate. - Be part of something bigger. Join a global community of linguists, subject matter experts, and language professionals who are advancing human knowledge together. - Grow without limits. As a Lilt contractor you get access to diverse, innovative projects that expand your portfolio and sharpen your skills across industries and domains. - Have fun doing what you love. Bring your language skills to life on projects that are as interesting as they are impactful. What to Consider Before Applying - Not ideal as a full time job or primary income source. Work availability fluctuates with project demand, making this better suited as a supplemental income stream. As a 1099 contractor, you won't receive benefits such as health insurance, paid time off, or retirement contributions, and hours are not guaranteed. - Requires reliable availability and commitment. Once you accept a task, we expect quality work and on-time delivery. Most tasks require a minimum of 2 hours per day or 10 hours per week. If your schedule is unpredictable, this may not be the right fit. - Geographic restrictions may apply. We cannot engage contractors in regions subject to international embargo or sanctions. As a 1099 contractor, you are solely responsible for your own tax obligations. We recommend consulting a tax professional before engaging. HOW TO JOIN OUR EXPERT COMMUNITY Step 1: Apply with the English-language version of your Resume/C.V. highlighting your expertise in the domain. Step 2: Register in Tipalti to ensure a smooth payment process. Step 3: Finalize onboarding and join the Production team. AI is changing how the world communicates — and LILT is leading that transformation. LILT's mission is to make the world's information available to everyone, no matter the language they speak. Join our global community who thrive on innovation and excellence. Our collective knowledge, uniqueness, and skills deliver multilingual AI and human-verified services to Enterprises, Governments, and AI Developers around the world. Earn money. Have fun. Advance human knowledge. Work on diverse projects from anywhere, any time you want. Get paid quickly and fairly, and build your professional network in a supportive community—all through a streamlined application process tailored to your expertise. Information collected and processed as part of your application process, including any job applications you choose to submit, is subject to LILT's Privacy Policy at https://lilt.com/legal/privacy. At LILT, we are committed to a fair, inclusive, and transparent hiring process. As part of our recruitment efforts, we may use artificial intelligence (AI) and automated tools to assist in the evaluation of applications, including résumé screening, assessment scoring, and interview analysis. These tools are designed to support human decision-making and help us identify qualified candidates efficiently and objectively. All final hiring decisions are made by people. If you have any concerns, require accommodations, or would like to opt-out of the use of AI in our hiring process, please let us know at recruiting@lilt.com. LILT is an equal opportunity employer. We extend equal opportunity to all individuals without regard to an individual’s race, religion, color, national origin, ancestry, sex, sexual orientation, gender identity, age, physical or mental disability, medical condition, genetic characteristics, veteran or marital status, pregnancy, or any other classification protected by applicable local, state or federal laws. We are committed to the principles of fair employment and the elimination of all discriminatory practices.

Location: Strava SF Workplace: Hybrid ABOUT STRAVA Strava is the app for active people. With over 200 million athletes in more than 185 countries, it’s more than tracking workouts—it’s where people make progress together, from new habits to new personal bests. No matter your sport or how you track it, Strava’s got you covered. Find your crew, crush your goals, and make every effort count. Start your journey https://www.strava.com/subscription with Strava today. Our mission is simple: to motivate people to live their best active lives. We believe in the power of movement to connect and drive people forward. ABOUT THIS ROLE Sport Science sits outside Product, Tech, and Runna, reporting directly to the CEO. The team is responsible for the ongoing scientific validation and safety of Strava's and Runna's fitness products, and for the applied research agenda that pushes forward the science of sport and fitness. As Head of Sport Science, you'll own two things at once: the ongoing scientific validation and safety review of Runna's and Strava's fitness products, and the applied research agenda behind them. You'll manage and grow academic partnerships, define the data and benchmarks needed to make our models' insights scientifically defensible, and grow a team over time. You'll work closely with the coaching team, AI/ML, Data Science, Product, Public Policy, and Legal. We follow a flexible hybrid model that translates to more than half of your time on-site in our San Francisco office, three days per week. WHAT YOU'LL DO: - Own the ongoing scientific validation and safety review of Runna's and Strava's fitness products, starting with the open items in an active academic audit - Manage and grow academic partnerships with Stanford University and Loughborough University, and scope new partnerships as needed - Define the data and label strategy, such as perceived exertion, injury history, and sleep, that makes our models' insights scientifically defensible, partnering closely with Data Science and AI/ML - Partner with Runna's coaching team on a recurring review cadence, serving as the scientific authority on disputed questions about the application of science in coaching - Build out the Sport Science team, plus an external academic advisory council, over time - Represent Strava's scientific credibility in external settings, from published research to occasional conference talks. WHAT YOU'LL BRING TO THE TEAM: - An MD, PhD, or equivalent applied track record in exercise physiology, sports science, biomechanics, sports medicine, or a closely related field - Substantial experience combining peer-reviewed research with applied work in industry, elite sport, or a research-focused sports medicine setting, translating science into product decisions - A track record of managing external academic or clinical partnerships, including agreements, multi-institution collaborations, and ethics-related governance - Comfort partnering with data science and ML teams to translate research questions into model and data requirements is a plus, though you won't need to write code yourself - Experience building a team or function from its first hire is a plus - A track record of representing scientific work externally, such as a paper, a conference talk, or a podcast, is a plus - Endurance or running-specific research experience is a plus, though not required WHY JOIN US? Movement brings us together. At Strava, we’re building the world’s largest community of active people, helping them stay motivated and achieve their goals. Our global team is passionate about making movement fun, meaningful, and accessible to everyone. Whether you’re shaping the technology, growing our community, or driving innovation, your work at Strava makes an impact. When you join Strava, you’re not just joining a company—you’re joining a movement. If you’re ready to bring your energy, ideas, and drive, let’s build something incredible together. Strava builds software that makes the best part of our athletes’ days even better. Just as we’re deeply committed to unlocking their potential, we’re dedicated to providing a world-class, inclusive workplace where our employees can grow and thrive, too. We’re backed by Sequoia Capital, TCV, Madrone Partners and Jackson Square Ventures, and we’re expanding in order to exceed the needs of our growing community of global athletes. Our culture reflects our community. We are continuously striving to hire and engage teammates from all backgrounds, experiences and perspectives because we know we are a stronger team together. Strava is an equal opportunity employer. In keeping with the values of Strava, we make all employment decisions including hiring, evaluation, termination, promotional and training opportunities, without regard to race, religion, color, sex, age, national origin, ancestry, sexual orientation, physical handicap, mental disability, medical condition, disability, gender or identity or expression, pregnancy or pregnancy-related condition, marital status, height and/or weight. 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. California Consumer Protection Act Applicant Notice https://docs.google.com/document/d/e/2PACX-1vSc8y6On4NlP5s12hf4kmWe_pvenVyQ78TbtVaz_clROhj9ADQ6kY4YScglBIuY2joKFKalOReX7vP_/pub

Location: Remote, Canada; Remote, Israel; Remote, United Kingdom; Remote, United States GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An overview of this role As a Staff Backend Engineer on GitLab's Security Factory: Code Scanning team, you help developers find and fix security issues. Those issues live in the code they write, and you set the technical direction for the static analysis engine that finds them. Your work spans two complementary parts of a complete security analysis. On the engine side, you shape how the static analysis toolkit models a program: parsing source into intermediate representations, resolving symbols, building call graphs, and tracking tainted data across files and languages. You define the architecture and specifications the team builds against, and you delegate component specifications within them to engineers and to the AI agents that implement them. On the evaluation side, you build and apply tooling that tests, measures, and validates what the engine finds against benchmark applications with known vulnerabilities. What the engine can model and how we measure what it finds are parts of one picture. As a Staff engineer you hold that picture, shape the long-range technical goals of the team, and raise the bar for every engineer on it. We build the engine with AI agents that write and review code from written specifications, under human direction. We expect you to direct that work effectively and with good judgment, and to help the team do the same. What you do Act as the directly responsible individual (DRI) for the team's highest-scope initiatives from design through delivery, shipping large features with minimal guidance and shaping the long-range goals of the team Bring systems built by one engineer to team ownership through documentation, tests, and shared review Set the technical direction for the AI-assisted tooling that implements, reviews, and validates engine changes and findings, design the checks that decide whether an agent-written change or generated result is fit to merge, and measure detection quality against benchmark applications with known vulnerabilities, raising the bar for what counts as a trustworthy result. That includes static application security testing (SAST) rules mapped to CWE and OWASP, and the test fixtures that prove they work. Own the architecture of the program model (parsing, symbol resolution, intermediate representations, call graphs, and taint and data-flow analysis) and of the pipeline that turns source code into findings, and define how both extend to new languages and frameworks Solve technical problems of the highest scope and complexity, actively seek out difficult impediments affecting the whole team, and advocate for improvements to quality, security, and performance with Product Management, UX, and partner teams such as Code Security and Composition Analysis Mentor all engineers on the team through code review and pairing, remove blockers to their autonomy, and shepherd the definition and improvement of our internal standards through review Participate in on-call rotations to assist troubleshooting product operations, security operations, and urgent engineering issues Define the overarching architecture and specification documents for the engine, delegate component specifications within them, and drive their implementation by AI agents and engineers working independently through phased plans, small reviewable units of change, and specifications kept in lockstep with the code Build and maintain the harness, agent instructions, and agentic skills that keep agent-written code trustworthy, including separate coding and reviewing agents, rules and tests the coding agents cannot change, independent review panels of agents from different model providers, and performance, API, and dependency gates, with risky changes escalated to human review Stay current with research in program analysis and security, run AI-assisted research and spikes, and turn the findings into prototypes, proposals, and upstream contributions, including responsible disclosure of findings in open source projects Take part in on-call or operational support where your team’s ownership model requires it What you bring Experience building your own LLM tooling, such as a harness, an agent pipeline, or evaluations, with the judgment to know when output is trustworthy and when it isn't Extensive professional experience writing, testing, and reviewing production code in Rust, Go, or a comparable systems language, with depth in at least one. The engine is Rust, the analyzer wrapper is Go, and the monolith integration is Ruby, and we value willingness to work across them. Experience with performance optimization and with containerized workflows and CI/CD (we use Docker heavily) A deep program analysis and static analysis background, such as parsing and ASTs, intermediate representations (SSA, control-flow and call graphs), taint and data-flow analysis, type inference, incremental and fixpoint computation, or writing detection rules, with the ability to read, evaluate, and apply the research literature Deep application security experience, such as vulnerability research, secure code review, or writing detection rules, and fluency with vulnerability classes (OWASP Top 10, CWE) Demonstrated capacity to communicate clearly and concisely about complex technical, architectural, and organizational problems, and to write architecture and design specifications that bring a team to a decision A track record of taking ownership of ambiguous, team-wide problems and shipping them from concept to production with minimal guidance, with specific, regular async updates on progress, blockers, risks, and next steps Experience defining a system's overarching architecture, delegating component specifications to engineers and AI agents, and getting them implemented reliably A track record of mentoring engineers, raising a team's technical bar, and influencing technical direction by achieving consensus with peers and leadership Helpful experience Familiarity with popular web or mobile application frameworks and how they handle input, data, and configuration Experience designing guardrails for agent-written code, such as mutation testing, fuzzing, and CI gates the coding agent cannot modify A record of engaging with the research community, such as publications, tool papers, or upstream open source contributions in program analysis or security About the team The Security Factory: Code Scanning team develops GitLab's SAST capabilities for customer software repositories. We work closely with the Code Security team on scanning rules & flows, with Composition Analysis on the broader software supply chain, and with other groups across the Sec Section. We rely heavily on asynchronous work across time zones. Remote-Global The base salary range for this role’s listed level is currently for residents of the United States only. This range is intended to reflect the role's base salary rate in locations throughout the US. Grade level and salary ranges are determined through interviews and a review of education, experience, knowledge, skills, abilities of the applicant, equity with other team members, alignment with market data, and geographic location. The base salary range does not include any bonuses, equity, or benefits. See more information on our benefits and equity . Sales roles are also eligible for incentive pay targeted at up to 100% of the offered base salary. United States Salary Range $152,800 — $259,200 USD How GitLab Supports Full-Time Employees Benefits to support your health, finances, and well-being Flexible Paid Time Off Team Member Resource Groups Equity Compensation & Employee Stock Purchase Plan Growth and Development Fund Parental Leave Please note that we welcome interest from candidates with varying levels of experience; many successful candidates do not meet every single requirement. Additionally, studies have shown that people from underrepresented groups are less likely to apply to a job unless they meet every single qualification. If you're excited about this role, please apply and allow our recruiters to assess your application. Country Hiring Guidelines: GitLab hires new team members in countries around the world. All of our roles are remote, however some roles may carry specific location-based eligibility requirements. Our Talent Acquisition team can help answer any questions about location after starting the recruiting process. Privacy Policy: Please review our Recruitment Privacy Policy. Your privacy is important to us. GitLab is proud to be an equal opportunity workplace and is an affirmative action employer. GitLab’s policies and practices relating to recruitment, employment, career development and advancement, promotion, and retirement are based solely on merit, regardless of race, color, religion, ancestry, sex (including pregnancy, lactation, sexual orientation, gender identity, or gender expression), national origin, age, citizenship, marital status, mental or physical disability, genetic information (including family medical history), discharge status from the military, protected veteran status (which includes disabled veterans, recently separated veterans, active duty wartime or campaign badge veterans, and Armed Forces service medal veterans), or any other basis protected by law. GitLab will not tolerate discrimination or harassment based on any of these characteristics. See also GitLab’s EEO Policy and EEO is the Law . If you have a disability or special need that requires accommodation , please let us know during the recruiting process .

Location: Strava SF Workplace: Hybrid ABOUT STRAVA Strava is the app for active people. With over 200 million athletes in more than 185 countries, it’s more than tracking workouts—it’s where people make progress together, from new habits to new personal bests. No matter your sport or how you track it, Strava’s got you covered. Find your crew, crush your goals, and make every effort count. Start your journey https://www.strava.com/subscription with Strava today. Our mission is simple: to motivate people to live their best active lives. We believe in the power of movement to connect and drive people forward. ABOUT THIS ROLE Our Technical Accounting and SEC Reporting team owns how Strava applies accounting standards and reports to the market. As we scale our reporting and technical accounting for the requirements of a public company, this team makes sure our conclusions are sound, documented, and ready for audit and regulatory scrutiny. In this role, you will set technical direction for the team and take increasing ownership of Strava's technical accounting areas as you onboard. You will work closely with the Accounting Director, lead an existing team member, and partner with Legal, FP&A, Revenue Accounting, external auditors, and outside counsel to resolve complex accounting questions and deliver SEC filings. We follow a flexible hybrid model that translates to more than half of your time on-site in our San Francisco office, three days per week. WHAT YOU'LL DO - Lead the evaluation of complex and novel accounting transactions, and document conclusions in memos that stand up to auditor and SEC scrutiny. - Own preparation and review of 10-K and 10-Q content, including technical disclosures. - Partner with external auditors and outside counsel, with the credibility to defend technical positions. - Build and run the technical accounting framework: policy library, memo standards, transaction intake and triage, and review controls. - Anticipate how new standards and regulatory changes affect Strava, and prepare the team ahead of them. - Coach and develop your direct report, and hold the team to a high bar for technical quality. - Work with Legal, FP&A, Revenue Accounting, and equity compensation partners to resolve issues and align on accounting positions. WHAT YOU'LL BRING TO THE TEAM - Hands-on experience preparing 10-K and 10-Q filings. - An Active CPA license and Big 4 public accounting experience. - A track record of sound technical accounting judgment, shown through memos you have authored and issues you have resolved. - The ability to work through issues with a range of cross-functional stakeholders, with a low-ego, solution-oriented approach. - Experience managing and developing people. - Experience supporting an IPO, an S-1, or a company's first years of public reporting is a plus. - Experience designing technical accounting policies and processes at a high-growth company is a plus. For more information on benefits, please click here https://docs.google.com/document/d/e/2PACX-1vTkFMPz3eCjd0FgQ28VWnK4d2BEnzGyaSFGwATR-dQdBb9HxZgay6kboqnT0-V-qaBDzSvYIzI76vT5/pub. WHY JOIN US? Movement brings us together. At Strava, we’re building the world’s largest community of active people, helping them stay motivated and achieve their goals. Our global team is passionate about making movement fun, meaningful, and accessible to everyone. Whether you’re shaping the technology, growing our community, or driving innovation, your work at Strava makes an impact. When you join Strava, you’re not just joining a company—you’re joining a movement. If you’re ready to bring your energy, ideas, and drive, let’s build something incredible together. Strava builds software that makes the best part of our athletes’ days even better. Just as we’re deeply committed to unlocking their potential, we’re dedicated to providing a world-class, inclusive workplace where our employees can grow and thrive, too. We’re backed by Sequoia Capital, TCV, Madrone Partners and Jackson Square Ventures, and we’re expanding in order to exceed the needs of our growing community of global athletes. Our culture reflects our community. We are continuously striving to hire and engage teammates from all backgrounds, experiences and perspectives because we know we are a stronger team together. Strava is an equal opportunity employer. In keeping with the values of Strava, we make all employment decisions including hiring, evaluation, termination, promotional and training opportunities, without regard to race, religion, color, sex, age, national origin, ancestry, sexual orientation, physical handicap, mental disability, medical condition, disability, gender or identity or expression, pregnancy or pregnancy-related condition, marital status, height and/or weight. 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. California Consumer Protection Act Applicant Notice https://docs.google.com/document/d/e/2PACX-1vSc8y6On4NlP5s12hf4kmWe_pvenVyQ78TbtVaz_clROhj9ADQ6kY4YScglBIuY2joKFKalOReX7vP_/pub