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Location: India Workplace: Remote TRANSACTION ADVISORY AI RESEARCHER (Due Diligence, Valuation) Full time | Remote — India ABOUT US Aptura is a London-based company working on understanding how AI is changing professional work. We look closely at how finance and advisory professionals actually work, and where AI helps or falls short. The company was founded by people with backgrounds at Lazard, McKinsey and Partners Group. ROLE DESCRIPTION We are looking for Subject Matter Experts from Big 4 deal advisory or strategy consulting who turn data rooms and market data into decks a client can act on. You know the difference between a slide that informs a decision and one that fills a page. You have used AI tools on your own work and been frustrated by the mistakes they make, or you simply want to find out how good they really are. You will turn that experience into realistic PowerPoint tasks that test how well AI do the deck work of an advisory analyst. RESPONSIBILITIES INCLUDE - Writing realistic PowerPoint tasks drawn from your own advisory work: building decks from source documents, filling corporate templates, rolling decks forward and making precise edits - Working through each task yourself so there is a clear, correct answer - Writing a yes-or-no checklist precise enough that an AI grader can mark any attempt against it NECESSARY SKILLS INCLUDE - 2+ years in transaction services, valuations, commercial due diligence or strategy consulting - Deep hands-on PowerPoint: native charts, tables and corporate templates - Ability to define what a correct deck looks like precisely enough for someone else to grade against it - Clear writing. Tasks must be written by you, not by AI tools - Attention to detail, and willingness to learn concepts in AI and data HOW IT WORKS 1. Apply with your details and CV. After applying, verify your email and choose an available 30-minute group walkthrough call. You can book immediately; there is no application-approval step before booking. 2. Attend the walkthrough and enter the code shared by the host at the end of the call to unlock your task workspace. 3. Create one original task from your own work in about 45 minutes. Submit the brief, the actual input files needed to complete it, a written expected result and at least five binary rubric checks, each with one skill tag. Input-file uploads are compulsory. 4. Write the brief and rubric yourself, without AI drafting, rewriting or polishing. Input materials must also be human-authored. Use only materials you are authorised to share, with confidential employer or client information removed. 5. Submit through your account for automated screening and team review. Follow any request for revisions in your account. Completing onboarding does not guarantee a job offer; selection remains subject to review. LOCATION Remote — India

Location: India Workplace: Remote INVESTOR RELATIONS AI RESEARCHER (Results Decks, Board Packs) Full time | Remote — India ABOUT US Aptura is a London-based company working on understanding how AI is changing professional work. We look closely at how finance and advisory professionals actually work, and where AI helps or falls short. The company was founded by people with backgrounds at Lazard, McKinsey and Partners Group. ROLE DESCRIPTION We are looking for Subject Matter Experts from investor relations or FP&A who own the quarterly cycle of results decks, board packs and KPI reporting. You know that rolling a deck forward is never just swapping numbers. You have used AI tools on your own work and been frustrated by the mistakes they make, or you simply want to find out how good they really are. You will turn that experience into realistic PowerPoint tasks that test how well AI do the deck work of an IR or FP&A analyst. RESPONSIBILITIES INCLUDE - Writing realistic PowerPoint tasks drawn from your own reporting cycle: building decks from source documents, filling corporate templates, rolling decks forward and making precise edits - Working through each task yourself so there is a clear, correct answer - Writing a yes-or-no checklist precise enough that an AI grader can mark any attempt against it NECESSARY SKILLS INCLUDE - 3+ years in investor relations, FP&A or financial reporting at a listed company or large corporate - Deep hands-on PowerPoint: native charts, tables and corporate templates - Ability to define what a correct deck looks like precisely enough for someone else to grade against it - Clear writing. Tasks must be written by you, not by AI tools - Attention to detail, and willingness to learn concepts in AI and data HOW IT WORKS 1. Apply with your details and CV. After applying, verify your email and choose an available 30-minute group walkthrough call. You can book immediately; there is no application-approval step before booking. 2. Attend the walkthrough and enter the code shared by the host at the end of the call to unlock your task workspace. 3. Create one original task from your own work in about 45 minutes. Submit the brief, the actual input files needed to complete it, a written expected result and at least five binary rubric checks, each with one skill tag. Input-file uploads are compulsory. 4. Write the brief and rubric yourself, without AI drafting, rewriting or polishing. Input materials must also be human-authored. Use only materials you are authorised to share, with confidential employer or client information removed. 5. Submit through your account for automated screening and team review. Follow any request for revisions in your account. Completing onboarding does not guarantee a job offer; selection remains subject to review. LOCATION Remote — India

Location: India Workplace: Remote INVESTMENT BANKING AI RESEARCHER (Pitch Books, Deal Decks) Full time | Remote — India ABOUT US Aptura is a London-based company working on understanding how AI is changing professional work. We look closely at how finance and advisory professionals actually work, and where AI helps or falls short. The company was founded by people with backgrounds at Lazard, McKinsey and Partners Group. ROLE DESCRIPTION We are looking for Subject Matter Experts from investment banking who have spent years building pitch books, teasers and deal decks. You know what a client-ready slide looks like, and how far most AI output still is from it. You have used AI tools on your own work and been frustrated by the mistakes they make, or you simply want to find out how good they really are. You will turn that experience into realistic PowerPoint tasks that test how well AI do the deck work of a junior banker. RESPONSIBILITIES INCLUDE - Writing realistic PowerPoint tasks drawn from your own deal work: building decks from source documents, filling corporate templates, rolling decks forward and making precise edits - Working through each task yourself so there is a clear, correct answer - Writing a yes-or-no checklist precise enough that an AI grader can mark any attempt against it NECESSARY SKILLS INCLUDE - 2+ years in M&A, ECM, DCM or leveraged finance at a bank or advisory boutique - Deep hands-on PowerPoint: native charts, tables and corporate templates - Ability to define what a correct deck looks like precisely enough for someone else to grade against it - Clear writing. Tasks must be written by you, not by AI tools - Attention to detail, and willingness to learn concepts in AI and data HOW IT WORKS 1. Apply with your details and CV. After applying, verify your email and choose an available 30-minute group walkthrough call. You can book immediately; there is no application-approval step before booking. 2. Attend the walkthrough and enter the code shared by the host at the end of the call to unlock your task workspace. 3. Create one original task from your own work in about 45 minutes. Submit the brief, the actual input files needed to complete it, a written expected result and at least five binary rubric checks, each with one skill tag. Input-file uploads are compulsory. 4. Write the brief and rubric yourself, without AI drafting, rewriting or polishing. Input materials must also be human-authored. Use only materials you are authorised to share, with confidential employer or client information removed. 5. Submit through your account for automated screening and team review. Follow any request for revisions in your account. Completing onboarding does not guarantee a job offer; selection remains subject to review. LOCATION Remote — India

Задачи: — искать информацию о компаниях, конкурентах, лидах, поставщиках и кандидатах; — собирать данные на LinkedIn, Telegram, Discord, джоб-бордах, форумах и нишевых ресурсах; — находить контакты и информацию, которую не всегда удаётся получить обычным поиском; — самостоятельно выходить на контакт, работать с аккаунтами, использовать AdsPower, прокси, базовый парсинг и автоматизацию; — проверять информацию по нескольким источникам и превращать большие объёмы данных в понятные структурированные отчёты. Требования: — опыт пользователя поисковых инструментов и нестандартных источников; — опыт Internet Research / Sourcing от 1–2 лет; — внимательность и самостоятельность, умение проверять достоверность информации; — английский от Intermediate+; — опыт в OSINT будет большим плюсом. Условия: — полностью удалённая работа; — график 5/2, 9:00–18:00 по Киеву; — полная занятость, онлайн-офис через Compass Space; — зарплата до $1500 в месяц; — работа в Армении. Требования к языкам: русский — свободно, английский — Intermediate+, желательно свободный.

Location: San Francisco, CA | New York City, NY | Seattle, WA 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 Reinforcement learning is how Claude learns to reason, write code, and act autonomously over long horizons. The RL Scaling team works on how RL scales: what happens to throughput, stability, and learning efficiency as models get larger, episodes get longer, and compute grows by orders of magnitude, and what has to change in our algorithms and systems to keep getting returns from that scale. This role sits squarely across research and engineering. You'll develop next-generation architectures and RL algorithms, take them from a small-scale result to a frontier-scale run, and understand every place they behave differently along the way. You'll build the systems that set how fast the team can iterate: how many experiments, at what scale, and how quickly we can trust the results. And you'll work on Anthropic's largest and fastest RL runs, where the gap between a good idea and a working one is often a problem no one has solved yet. Key responsibilities Study how RL training and sampling scale with model size, context length, and compute, and find the algorithmic and systems changes that keep scaling efficient Develop next-generation model architectures and RL algorithms, and make them run efficiently at frontier scale Take promising small-scale results to frontier-scale runs, and diagnose why they behave differently when they get there, whether the cause is numerical, algorithmic, or systemic Build the experimental infrastructure that sets research velocity: fast, reproducible comparisons of architecture and algorithm variants at meaningful scale Own end-to-end performance of our largest RL runs, from research code down to the hardware Build performance and cost models for proposed architecture and algorithm changes, and use them to decide which ideas get scaled Investigate training dynamics at scale, including instabilities, divergence, and throughput regressions, and trace them to root cause Minimum qualifications Deep familiarity with modern transformer language models, including their architecture, training dynamics, and the behavior of large-scale optimization Hands-on experience training large models in a distributed setting, including the tradeoffs between data, tensor, and pipeline parallelism A track record of original technical work in ML training or systems, such as new methods, architectures, or optimizations, demonstrated through research, open-source, or production impact Ability to design rigorous experiments at scale, including baselines, ablations, and enough statistical care to trust a result that costs real compute Ability to reason quantitatively about the compute, memory, and communication costs of a model or algorithm Strong programming skills in Python and JAX or PyTorch, and comfort reading and changing code at every layer of the stack Preferred qualifications Research experience in reinforcement learning, optimization, or large-scale training, published or otherwise Experience developing RL algorithms for language models Experience with scaling laws or other quantitative models of training efficiency Experience designing or modifying transformer architectures beyond standard configurations Experience scaling training to large fleets of accelerators and debugging the problems that only appear at scale Deep understanding of numerics in large-scale training, including low-precision formats and sources of instability Familiarity with how GPU or TPU performance characteristics shape architecture and algorithm choices Experience with C++ or Rust Representative projects Characterize how a new RL algorithm's throughput and learning efficiency change from small models to frontier scale, and fix what breaks Develop a new attention variant, get it working at full scale, and measure how its quality and throughput compare to the baseline Prepare our next largest-ever RL run: find what breaks when model size, context length, and compute all grow at once, and fix it before launch Trace a loss instability that only appears past a certain scale to its root cause, and work out whether the fix belongs in the algorithm, the numerics, or the system Build a model that predicts the throughput and cost of a proposed architecture change before anyone writes the kernel 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: $500,000 — $850,000 USD 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: San Francisco, CA | New York City, NY | Seattle, WA 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 Reinforcement learning is how Claude learns to reason, write code, and act autonomously over long horizons. At frontier scale, an RL run is an unusually demanding distributed system. Training, sampling, and environment execution run concurrently across a large fleet of accelerators and hosts, exchange data continuously, and have to keep making progress while hardware fails, load shifts, and the research changes underneath them. How well that system holds together determines how much of our compute turns into learning, and how quickly the team can try the next idea. As a Research Engineer on the Distributed Systems team within RL Engineering, you'll work on whatever part of that system is the current limit. That might be scheduling and placement, data movement between components, running large numbers of sandboxed environments, storage and checkpointing, networking, fault tolerance, autoscaling, or the observability that tells us what a run is actually doing. We're looking for generalists: engineers who can move between these layers, reason from first principles about a system they haven't seen before, and pick the problem that matters most rather than the one closest to their prior experience. Our system changes as fast as the research does, correctness under failure matters as much as throughput, and the best solutions often come from understanding the ML workload well enough to know which guarantees it actually needs. Strong candidates have built and run large distributed systems, care about getting the details right, and want to apply that experience to a workload that is very large, very heterogeneous, and changing quickly. Key responsibilities Design, build, and operate the distributed systems that run RL at scale, across training, sampling, and environment execution Find and remove whatever currently limits the system, whether it's scheduling, data movement, storage, networking, or coordination Build fault tolerance into every layer: failure detection, isolation, and recovery that keep long-running jobs making progress without human intervention Design resource management and autoscaling so that compute follows demand as a run's needs shift Build observability that makes it possible to understand what a run is doing and why it slowed down, stalled, or produced unexpected results Build automation that detects and remediates common problems, and design interfaces that let engineers and automated tools operate runs safely Work with researchers and performance engineers to make sure systems changes preserve training correctness and don't introduce subtle nondeterminism Remove classes of failure at their source through incident review, testing, and redesign, and write clear design documents for what you build Minimum qualifications Strong software engineering skills in Python and at least one systems language such as Rust, C++, or Go Experience designing, building, and operating large-scale distributed systems in production Deep understanding of distributed systems fundamentals, including consistency, coordination, consensus, failure modes, and recovery Ability to reason quantitatively about throughput, latency, and resource costs across compute, memory, storage, and network Experience debugging complex failures across many hosts and services, including failures you can't reproduce locally Strong written communication, including design documents and incident writeups Preferred qualifications Experience running ML training or inference infrastructure at scale Experience across several layers of the stack, such as scheduling, storage, networking, and orchestration Experience building schedulers, autoscalers, or resource management systems Experience with container orchestration such as Kubernetes, and with sandboxed or virtualized code execution at scale Experience with high-performance networking, RDMA, or collective communication libraries Experience building observability or automated remediation for large fleets Experience with async Python frameworks such as Trio or asyncio Familiarity with reinforcement learning or large language model training workloads Representative projects Design a scheduler that places training, sampling, and environment work across a heterogeneous cluster while respecting network topology and failure domains Build a failure detection and recovery system that lets a long-running job survive host and network failures with minimal lost work Scale environment execution substantially without increasing tail latency for the training step Design an autoscaling policy that rebalances compute across components as a run's bottleneck shifts Build a diagnostics system that explains why a run's throughput dropped and proposes a fix Trace a rare data corruption bug across many services to a race condition in a recovery path, and redesign the path so the class of bug can't recur Design the operational interface for a run so that automated tools can safely diagnose and adjust it under human oversight 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: $500,000 — $850,000 USD 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: San Francisco, CA 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 We are seeking an experienced public opinion researcher to build and expand Anthropic's in-house polling and research function. This role will be fundamental to understanding how key audiences — from policymakers and third-party groups to the general public — perceive and respond to Anthropic's policy positions, messages, and campaigns. This is a foundational role: you'll establish the research function from the ground up, with high autonomy and limited precedent. The Central Policy team sits at the operational heart of Anthropic's policy function — distinct from government relations and communications, but essential to enabling both. You'll work cross-functionally to ensure our policy and communications strategy is grounded in a rigorous understanding of stakeholder sentiment. The polling insights you generate will directly feed into high-visibility campaigns and will be a key asset in our policy efforts in Washington and beyond. Anthropic is equal parts research lab, policy think-tank, and technology startup. We care deeply about the safe development of AI systems and build partnerships with governments through proactive, opinionated, substantive policy conversations. This role offers a unique opportunity to be at the forefront of AI policy, bringing rigorous research discipline to policy strategy. Success in this role means establishing trusted relationships with leading polling firms around the world, delivering high-quality research on a regular cadence, and becoming the internal expert on how key audiences perceive AI, Anthropic, and Anthropic's positions and messages. You'll translate polling insights into strategic recommendations that measurably improve campaign effectiveness, and build scalable processes that allow the function to grow efficiently as demand increases. Key responsibilities Develop a comprehensive strategy for our in-house political research function that aligns with Anthropic's policy goals Identify, evaluate, and establish relationships with leading research and polling firms, ensuring coverage across demographics, geographies, and political perspectives Conduct detailed, proactive research to test core messages, policy proposals, and campaign themes, and to evaluate Anthropic's brand perception and performance Execute rapid-response polling to quickly assess Anthropic's messaging strategy in response to external events, policymaker actions, competitive developments, or emerging opportunities Work with external affairs colleagues (federal, state, and international) and policy communications to identify research priorities, interpret findings, and translate insights into actionable strategic recommendations Develop and maintain a knowledge management system for polling data, insights, and recommendations that ensures findings are accessible and actionable Manage polling vendors at scale, including vendor performance management Participate in strategy sessions and provide thought partnership on the design of messages, policy proposals, and campaigns ahead of polling and testing Create clear, compelling deliverables that distill polling findings into insights and recommendations Identify opportunities to build and scale the polling function over time, including staffing needs, process improvements, and capability expansion Track and report on the impact and utility of research, measuring how insights translate into more effective campaigns and strategic decisions Minimum qualifications Experience designing and executing public opinion research, including survey and questionnaire design, sampling approaches, and message testing Ability to analyze quantitative and qualitative polling data and translate findings into clear, decision-ready written recommendations Experience selecting, briefing, and managing external polling or research vendors Strong writing and presentation skills, including distilling complex research for senior, non-technical audiences Preferred qualifications 8+ years of professional experience in political or public opinion research, ideally spanning multiple campaign cycles and policy environments Corporate public affairs experience, ideally in a highly scrutinized or regulated industry Strategic thinking that spots emergent issues, identifies and tests the right messages, and translates those insights into tactical recommendations A track record of building relationships with vendors, external experts, and complex stakeholder ecosystems Strong organizational skills, with the ability to manage multiple projects simultaneously, maintain clear priorities, and deliver on tight timelines Comfort operating in ambiguous environments, taking ownership of problems, and proactively driving initiatives with limited precedent A resourceful, collaborative working style and genuine commitment to being a strong teammate Passion for AI policy and alignment with Anthropic's safety mission and commitment to responsible AI development 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: $230,000 — $265,000 USD 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: New York, New York, United States About the Role iCapital is looking to hire a Head of Research and Market Development to build and lead iCapital's market intelligence function, delivering actionable insights across private markets, wealth management, and financial technology. This role combines market research, client and advisor insights, competitive intelligence, and business analysis to inform strategic decision-making across Product, Marketing, Sales, Distribution, Corporate Development, and executive leadership. This individual will translate complex market dynamics into clear recommendations that strengthen iCapital's competitive position, identify growth opportunities, and support long-term business expansion. Working across global teams and external partners, this individual will establish the frameworks, governance, and reporting capabilities needed to scale a best-in-class market intelligence function. This role will serve as a trusted advisor to senior leadership while advancing iCapital's position as a thought leader in the evolving wealth and alternatives landscape. Responsibilities Build and lead a centralized market intelligence function, including its vision, operating model, governance framework, roadmap, and long-term team structure. Develop scalable research, reporting, dashboards, executive briefings, and knowledge-sharing resources that support enterprise-wide decision-making. Serve as the firm's central resource for market research, client and advisor insights, competitive intelligence, market development initiatives, and external research relationships. Monitor market, competitive, regulatory, and industry trends across investment management, wealth management, financial technology, private markets, hedge funds, structured investments, insurance, retirement, and advisor distribution. Produce market landscape assessments, opportunity analyses, adoption studies, and business intelligence that inform strategic planning and commercial priorities. Partner with Product, Marketing, Sales, Distribution, Corporate Development and Strategy, and international business leaders to inform product strategy, positioning, messaging, growth initiatives, and expansion opportunities. Identify emerging market opportunities, competitive whitespace, partnership opportunities, and evolving client needs that support innovation and platform differentiation. Design and lead primary research initiatives while delivering executive presentations, strategic recommendations, and thought leadership that promote market awareness and data-driven decision-making across the organization. Qualifications 15+ years of experience in market research, market intelligence, strategy, consulting, business insights, or related functions within financial services, wealth management, asset management, alternatives, or fintech MBA or equivalent advanced degree is preferred Proven experience building, scaling, and leading market intelligence, market development, strategic insights, or research organizations Deep understanding of private markets, alternative investments, advisor distribution, wealth management, portfolio construction, and related investment products and platforms Strong analytical, strategic, and problem-solving skills with the ability to synthesize complex data, market dynamics, and business trends into actionable recommendations Demonstrated success influencing senior executives, advising cross-functional stakeholders, and driving enterprise-wide initiatives Exceptional written, verbal, and presentation skills with experience delivering executive-level insights and recommendations Experience leveraging market research, competitive intelligence, analytics platforms, and external industry relationships to support business growth and decision-making Benefits The base salary range for this role is $190,000 to $215,000.  iCapital offers a compensation package which includes salary, equity for all full-time employees, and an annual performance bonus. Employees also receive a comprehensive benefits package that includes an employer matched retirement plan, generously subsidized healthcare with 100% employer paid dental, vision, telemedicine, and virtual mental health counseling, parental leave, and unlimited paid time off (PTO). We believe the best ideas and innovation happen when we are together. Employees in this role will work in the office Monday-Thursday, with the flexibility to work remotely on Friday. For additional information on iCapital, please visit https://www.icapitalnetwork.com/about-us Twitter: @icapitalnetwork | LinkedIn: https://www.linkedin.com/company/icapital-network-inc | Awards Disclaimer: https://www.icapitalnetwork.com/about-us/recognition/ iCapital is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, gender, sexual orientation, gender identity, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.

Location: Andorra la Vella, Andorra; Buenos Aires, Argentina; Brasilia, Brazil; Rio de Janeiro, Brazil; Barcelona, Spain; Madrid, Spain; Milano, Italy; Rome, Italy; Abu Dhabi, United Arab Emirates; London, United Kingdom; Lugano, Switzerland; Warsaw, Poland; Amsterdam, Netherlands; Lisbon, Portugal; Dublin, Ireland; Bucharest, Romania; Bangalore, India; Kuala Lumpur, Malaysia 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 model team, you will drive innovation in model serving and inference architectures for advanced AI systems. Your work will focus on optimizing model deployment and inference strategies to deliver highly responsive, efficient, and scalable performance across real-world applications. You will work on a wide spectrum of systems, ranging from resource-efficient models designed for limited hardware environments to complex, multi-modal architectures that integrate data such as text, images, and audio. We expect you to have deep expertise in designing and optimizing model serving pipelines and inference frameworks as well as a strong background in advanced model architectures. You will adopt a hands-on, research-driven approach to develop, test, and implement novel serving strategies and inference algorithms. Your responsibilities include engineering robust inference pipelines, establishing comprehensive performance metrics, and identifying and resolving bottlenecks in production environments. The ultimate goal is to enable high-throughput, low-latency, low-memory footprint, and scalable AI performance that delivers tangible value in dynamic, real-world scenarios. Responsibilities Design and deploy state-of-the-art model serving architectures that deliver high throughput and low latency while optimizing memory usage. Ensure these pipelines run efficiently across diverse environments, including resource-constrained devices and edge platforms. Establish clear performance targets such as reduced latency, improved token response, and minimized memory footprint. Build, run, and monitor controlled inference tests in both simulated and live production environments. Track key performance indicators such as response latency, throughput, memory consumption, and error rates, with special attention to metrics specific to resource-constrained devices. Document iterative results and compare outcomes against established benchmarks to validate performance across platforms. Identify and prepare high-quality test datasets and simulation scenarios tailored to real-world deployment challenges, specifically those encountered on low-resource devices. Set measurable criteria to ensure that these resources effectively evaluate model performance, latency, and memory utilization under various operational conditions. Analyze computational efficiency and diagnose bottlenecks in the serving pipeline by monitoring both processing and memory metrics. Address issues such as suboptimal batch processing, network delays, and high memory usage to optimize the serving infrastructure for scalability and reliability on resource-constrained systems. Work closely with cross-functional teams to integrate optimized serving and inference frameworks into production pipelines designed for edge and on-device applications. Define clear success metrics such as improved real-world performance, low error rates, robust scalability, optimal memory usage and ensure continuous monitoring and iterative refinements for sustained improvements. 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). Must have knowledge of Metal Shading Language (MSL). You should be comfortable writing custom compute shaders from scratch. Proven experience in low-level kernel optimizations and inference optimization on mobile devices is essential. Your contributions should have led to measurable improvements in inference latency, throughput, and memory footprint for domain-specific applications, particularly on resource-constrained devices and edge platforms. A deep understanding of modern model serving architectures and inference optimization techniques is required. This includes state-of-the-art methods for achieving low-latency, high-throughput performance, and efficient memory management in diverse, resource-constrained deployment scenarios. Must have strong expertise in writing GPU kernels for mobile devices (i.e., smartphones) as well as a deep understanding of model serving frameworks and engines. Practical experience in developing and deploying end-to-end inference pipelines, from optimizing models for efficient serving to integrating these solutions on resource-constrained devices is required. Demonstrated ability to apply empirical research to overcome challenges in model serving, such as latency optimization, computational bottlenecks, and memory constraints. You should be proficient in designing robust evaluation frameworks and iterating on optimization strategies to continuously push the boundaries of inference performance and system efficiency. Distributed Inference Systems: Designing and optimizing high-performance inference engines using techniques like Tensor Parallelism, Pipeline Parallelism, and Expert Parallelism to handle massive models on GPU clusters. Deep understanding of the math and structure behind Diffusion Models and Vision Transformers Understanding of Pruning, Quantization, Flash attention, KV Cache, Speculative Decoding (Eagle) etc. 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; Zurich; Warsaw; London 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. ABOUT THE RESEARCH ENGINEERING TEAM   The team spans Platform (shared infra & clean code) and Embedded (inside research squads). Engineers can move along the research↔production spectrum as needs or interests evolve.   As a Research Engineer – ML track, you’ll build and optimise the large-scale learning systems that power our open-weight models. Working hand-in-hand with Research Scientists, you’ll either join:   - Platform RE Team: Enhance the shared training framework, data pipelines and cluster tooling used by every team; or - Embedded RE Team: Sit inside a research squad (Alignment, Pre-training, Multimodal, Safety …) and turn fresh ideas into repeatable, scalable code.     What You Will Do   • Accelerate researchers by taking on the heavy parts of large-scale ML pipelines and building robust tools. • Interface cutting-edge research with production: integrate checkpoints, streamline evaluation, and expose APIs. • Design, implement and benchmark ML algorithms; write clear, efficient code in Python. • Deliver prototypes that become production-grade components for Vibe and our enterprise API.   What We're Looking For   • Master’s or PhD in Computer Science (or equivalent proven track record). • 4 + years working on large-scale ML codebases. • Hands-on with PyTorch, JAX or TensorFlow; comfortable with distributed training (DeepSpeed / FSDP / SLURM / K8s). • Experience in deep learning, NLP or LLMs; bonus for CUDA or data-pipeline chops. • Strong software-design instincts: testing, code review, CI/CD. • Self-starter, low-ego, collaborative.   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.

Задачи: — разработка, тестирование и внедрение ИИ-агентов (в том числе LLM-as-a-Judge) и классических ML-моделей для оценки качества, детекции аномалий, прогнозирования деградации и автоматической локализации причин сбоев — исследование и внедрение новых подходов в области настройки LLM, LLM-as-a-Judge и RAG, чтобы сделать мониторинг точнее, стабильнее и понятнее — ведение проекта по полному циклу: от идеи и прототипа до рабочего решения в проде, его тестирования и поддержки — проектирование пайплайнов для работы с данными (трейсами агентов) и обучения моделей, интегрируя их в нашу MLOps экосистему — взаимодействие с командами разработки и валидации ИИ-агентов, MLOps для интеграции решений и формирования лучших практик. Требования: — глубокое знание математической статистики, алгоритмов классического ML и архитектур нейросетей — опыт работы от 5 лет в роли Data Science / Machine Learning с полным циклом разработки — от исследований и прототипирования до внедрения в прод и мониторинга — опыт проведения аналитических исследований (R&D): умение самостоятельно изучать проблемную область, формулировать и проверять гипотезы, выбирать и адаптировать state-of-the-art методы под задачи проекта — уверенное владение стеком технологий для анализа, экспериментов и разработки: NumPy, Pandas, Polars, Scikit-learn, XGBoost, LightGBM, CatBoostOptuna / Hyperopt — навык написание чистого, модульного кода на Python, понимание принципов SOLID, опыт работы с Git. Будет преимуществом: — опыт разработки ИИ-агентов / агентных систем, понимание принципов их работы, коммуникации и оркестрации — опыт работы с трейсами и метаданными ИИ-агентов (OpenAI, Arize Phoenix, LangSmith) — опыт работы с векторными базами данных — знание observability-стека (OpenTelemetry, Prometheus, Grafana) для мониторинга ML-систем — публикации или значимый вклад в open-source в области ML/NLP/LLM. Условия: — комфортный современный офис: г. Москва, метро Кутузовский пр. — формат работы– офис, по согласованию с руководителем возможно выполнение пула задач в гибридном формате — ежегодный пересмотр зарплаты, годовая премия — корпоративный спортзал и зоны отдыха — более 400 образовательных программ СберУниверситета для профессионального и карьерного развития — программа адаптации и помощь руководителя на старте — расширенный ДМС (медицинское страхование), льготное страхование для семьи — ипотека для сотрудников — бесплатная подписка СберПрайм+, скидки на продукты компаний-партнеров — вознаграждение за рекомендацию друзей в команду Сбера.

Location: San Francisco Bay Area, USA Workplace: Hybrid Why work at Higgsfield AI? Higgsfield AI is the fastest-scaling generative AI company in history, hitting $1B in annual revenue run rate, 30M+ users worldwide, 6M+ generations per day, and powering 390 of Fortune 500 brands. We're building at the absolute frontier of AI-powered video creation and next-generation creative tools. Joining Higgsfield means becoming part of a high-impact team shaping the future of AI-native experiences, at a company that isn't just moving fast, but rewriting what fast looks like. About the role: We are looking for an Investor Relations Manager, Capital Markets & Strategic Research to build and deepen Higgsfield’s relationships across investment banks, equity research, institutional investors, and the broader capital markets ecosystem. This is not a traditional IR role focused on quarterly earnings, filings, or maintaining an investor database. As a private, fast-growing AI company, our goal is to establish Higgsfield as a primary source of insight for the financial community on Creative AI and the transformation of the broader creative economy. You will build relationships with the analysts, bankers, and investors shaping how emerging technology categories are understood, helping ensure they have the data, context, and access needed to understand the size of the market and Higgsfield’s position within it. The goal is not paid placement. It is to build the relationships and credibility that lead analysts to independently recognize Higgsfield as one of the companies defining the Creative AI category. What you'll do: - Build and manage relationships with investment bankers, equity and thematic research analysts, institutional and private-market investors, hedge funds, and other influential members of the capital markets ecosystem. - Establish a systematic engagement program with research teams at leading investment banks. - Develop a regular cadence of analyst briefings, executive conversations, and relationship-building across Wall Street. - Track relevant research covering Creative AI, generative video, the creator economy, advertising, media, AI infrastructure, and adjacent markets. - Make Higgsfield a trusted resource for analysts by providing market intelligence, data, executive access, and informed perspectives on how AI is transforming creative industries. - Educate analysts and bankers on the size and structure of the Creative AI opportunity and why the relevant TAM extends across multiple large existing industries. - Identify upcoming sector reports and research initiatives where Higgsfield can provide insight and contribute to the underlying investment thesis. - Create opportunities for earned inclusion of Higgsfield in thematic and sector research. - Identify opportunities to collaborate on or co-commission credible research examining Creative AI and the transformation of the creative economy, while maintaining a clear distinction between sponsored research and independent analyst coverage. - Partner with Higgsfield leadership, communications, and finance to develop the data, market frameworks, benchmarks, and narratives needed to explain the category. - Track analyst and banking relationships, engagements, relevant reports, upcoming research themes, and resulting outcomes. - Build a deliberate strategy for converting relationships into tangible outcomes rather than treating relationship-building itself as the objective. Requirements: - 3–6+ years of experience in investor relations, investment banking, equity research, capital markets communications, strategic financial communications, or a closely related field. - Strong understanding of how Wall Street research is produced and how relationships with analysts and investment banks are built. - Ability to discuss TAM, industry structure, competitive positioning, and technological disruption with sophisticated financial audiences. - Ability to translate a fast-moving technology story into a credible capital markets thesis without turning it into marketing language. - Highly relationship-driven while remaining focused on measurable outcomes. - Strong written and verbal communication skills with the ability to work closely with senior executives and cross-functional teams. - Comfortable operating in a fast-moving environment where the category, company, and market narrative are evolving quickly. *Nice to have: - Existing relationships across investment banks, equity research analysts, institutional investors, or the broader capital markets community. - Experience covering or working within AI, technology, internet, media, advertising, the creator economy, or high-growth private technology companies. - Experience working with thematic or sector research and understanding how emerging technology categories become incorporated into broader investment theses. - Experience helping position a private, high-growth company with sophisticated financial audiences. Compensation & Benefits - We offer a competitive and thoughtfully structured compensation package designed to align with impact, experience, and long-term growth. - Base Salary: The anticipated salary range for this role is $175,000 - $240,000, depending on experience, skills, scope, and location. - Bonus: This role is Bonus eligible and may participate in the Company's discretionary annual bonus program. - Equity: In addition to cash compensation, employees are eligible to participate in the company’s stock option program and share in Higgsfield’s long-term growth. - Benefits: We offer a comprehensive benefits package designed to support employees professionally and personally, including medical, dental, and vision insurance, a competitive 401(k) retirement plan with company matching, and additional benefits and perks. - The opportunity to work on ambitious AI products alongside a highly experienced, fast-moving, and international team. - Significant ownership, direct impact, and opportunities for professional growth as the company scales. This is a hybrid role based in the San Francisco Bay Area. Team members are expected to work from our San Francisco office three full days per week, with the remaining days worked remotely and are expected to be available during agreed working hours and to maintain sufficient overlap with the relevant team’s time zone. We value in-person collaboration, active communication, responsiveness, and close partnership across teams. Higgsfield AI is an equal opportunity employer. We are committed to building a diverse and inclusive team and do not discriminate on the basis of race, color, religion, sex, gender identity or expression, sexual orientation, national origin, age, disability, veteran status, or any other protected characteristic.

Задачи: — искать специалистов на международном рынке: США, Канада, Австралия, UK, Европа — работать с LinkedIn, Google / X-Ray Search, Boolean Search, профессиональными сообществами и базами — самостоятельно формировать поисковые запросы, target-листы компаний и стратегию поиска — работать с разными направлениями: FinTech, Payments, Product, AI / ML, SaaS, Consumer Tech, Business Требования: — опыт в роли Talent Sourcer / Researcher / Analyst от 1 года — уверенная работа с LinkedIn, желательно наличие прогретого аккаунта — владение Boolean Search и X-Ray Search — английский B2+ для работы с англоязычными профилями и письменной коммуникации Будет плюсом: — опыт в FinTech / Payments / Banking / SaaS / Consumer Tech Условия: — фикс от 700$ + KPI + бонусы — формат: fulltime, remote

Location: Paris Workplace: Hybrid 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 ROLE Cybersecurity is one of the areas where AI could do the most good — and one where the capability must be built with particular care. As a Research Engineer on this track, you'll push our models' capabilities in vulnerability discovery and remediation, security analysis, incident response, and across the offensive-to-defensive spectrum of cybersecurity, and it will be your job to develop that ability deliberately and safely. The work sits at the meeting point of research and engineering: you'll devise new approaches and be the one to implement them. Concretely, that means designing and building RL environments that reproduce realistic security scenarios, pipelines that generate synthetic training instances at scale, and experiments and evaluations that show what our models can actually do. Your results feed directly into the production training runs that shape our frontier models, in close collaboration with Mistral's researchers, engineers, and security specialists. Security specialists and ML engineers are both welcome here — what matters is that you can hold your own in both worlds, and are eager to go deeper on the one you know less. WHAT YOU WILL DO - Design and implement RL environments simulating cybersecurity scenarios. - Build the pipelines and infrastructure that generate synthetic cybersecurity training instances at scale — thousands of scenarios, not one hand-crafted exercise. - Conduct experiments and evaluations of model capabilities on these environments, from quick prototypes to controlled benchmark runs. - Own the infrastructure behind the environments: containers, sandboxes, VMs, cloud deployments, and orchestration (Kubernetes), all managed as code. - Partner with researchers and security specialists across Mistral, distilling their domain expertise into reproducible environments and datasets. - Write clear, efficient code in Python and enforce strong software-design practices: testing, code review, CI/CD. WHAT WE'RE LOOKING FOR - Hands-on expertise in offensive and/or defensive cybersecurity: vulnerability analysis, web/network/cloud security, secure coding practices, and SOC. - Strong software engineering skills: clean, reliable, well-tested code — not just exploit scripts. - Fluency in Python plus comfort reading lower-level languages (C/C++) for vulnerability analysis. - DevOps experience: Docker, Kubernetes, cloud deployments, sandboxed or simulated environments. - A pragmatic research-to-engineering mindset: ship a working first version, then refine and scale it. - Working knowledge of RL techniques and LLM training methodologies, or strong motivation to develop it. - Self-starter, low-ego, collaborative — comfortable working across research and engineering. NICE-TO-HAVES - CTF, cyber-range, or bug-bounty experience — as a player, challenge author, or platform builder. - A research background in cybersecurity, academic or industrial, or in another experimental discipline. - Prior experience building RL environments or large-scale ML training infrastructure. - Relevant open-source contributions and projects. 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.

Location: Singapore 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. ABOUT THE JOB Mistral AI is seeking Applied Scientists and Research Engineers focused on robotics. You will design, train, and deploy SOTA robotics models (VLM, VLA models for navigation and manipulation) and apply them to diverse use cases. You'll work cross-functionally with internal and external science, engineering, and product teams to deliver high-impact AI solutions. WHAT YOU WILL DO - Run pre-training, post-training and deploy state of the art models on large clusters. - Generate and curate datasets (image-text, video-text), and build evaluators/benchmarks for perception, navigation and manipulation tasks. - Develop the necessary tools and frameworks to facilitate data generation, model training, evaluation and deployment. - Collaborate with cross-functional teams to tackle complex use cases. - Manage research projects and communications with client research teams. ABOUT YOU - Fluent in English with excellent communication skills. - Expert with PyTorch or JAX. - Experience with Vision Language Models (VLM), Vision-Language-Action (VLA) models, perception, navigation and manipulation, simulation tools (e.g. Isaac SIM). - Clean, readable, high-performance Python code. - Doesn't need roadmaps. Ships. - Low-ego, collaborative and eager to learn. - Track record of success through personal projects, professional projects or academia. NICE TO HAVE - PhD / Master in a relevant field (Robotics, Machine Learning). - Research experience in robotics navigation, perception, manipulation. - Contributions to a large open-source or industry codebase. - Publications in top academic journals or conferences. - Enjoys improving existing code: typing, tests, CI pipelines. 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.

Location: Berlin Workplace: Hybrid adjoe builds the technologies behind mobile app growth and monetization, challenging the status quo of adtech by redefining how apps acquire users and generate revenue. Our two products, Playtime Arcade and adjoe Ads, sit at opposite ends of the mobile advertising spectrum: rewarded engagement and programmatic in-app advertising. Together they run on 13% of the world's smartphones, connecting advertisers, publishers, and hundreds of millions of users, with one goal: making mobile advertising work better for everyone in the ecosystem. Next-Gen Machine Intelligence for Scalable Discovery & Engagement The Data Science Research team builds foundational ML representations and advanced AI capabilities that enhance both Playtime and adjoe Ads. Operating as a horizontal deep-tech layer, the team leverages advanced AI and deep learning approaches—specifically generative approaches —to deliver critical systems such as high-dimensional user embeddings, general content understanding and sequential recommendation. These frameworks scale adjoe's products beyond standard industry limitations, utilizing behavioral and transactional data from over 770 million users. The team operates at the intersection of bleeding-edge R&D and high-scale production engineering, acting as the company’s internal science bar raiser and primary consulting layer for complex ML bottlenecks. The stack is optimized for deep learning and heavy data throughput: PyTorch and [Ray/Hugging Face] for training and fine-tuning foundation models, Trino and Athena for querying massive user-behavior data lakes, and dedicated GPU infrastructure for heavy workloads. The full lifecycle of these AI capabilities is owned by the team—from academic paper translation and offline prototyping to deploying core algorithmic frameworks built to sustain high-throughput, realtime production environments. Your Mission & Who We Are Looking For: - PhD or equivalent research depth, with a production track record. You have a PhD in CS, Statistics, Math, or Physics, or an MSc with extensive industry research, and publications in top-tier venues like SIGIR, KDD, NeurIPS, or ICLR. You've spent 4+ years building large-scale recommender systems in high-throughput environments: AdTech, e-commerce, or social. - You translate research into production, not just prototypes. You distill SOTA research into robust, production-ready code optimized for sub-millisecond latency. At adjoe, that means architecting multi-stage recommendation pipelines, Generative Retrieval, Deep Ranking, and Re-ranking, serving millions of requests across a stack built on 770 million users' behavioral data. - Deep expertise in PyTorch and large-scale model optimization. You have hands-on experience with high-concurrency optimization, model quantization, and distillation, the engineering side of getting large generative models to run under extreme production constraints, not just in research environments. - Content understanding and embeddings are core to your work. You research and develop information-rich user and ad embeddings using unsupervised and generative approaches, directly improving the quality of predictions across both Playtime and adjoe Ads. - Raises the technical bar around them. You lead architectural debates, mentor junior scientists, and drive the team's research direction without needing a roadmap handed to you. 🌎 We welcome applications from talent worldwide and provide relocation support to Hamburg, Germany for those ready to join our team. What’s in It for You? At adjoe, you’re not here to just close JIRA tickets, you’re helping build the infrastructure behind one of the most impactful platforms in adtech. The systems you work on will reach hundreds of millions of users and power billions of decisions every day. - Go Big. Own projects with impact on 770M users and push adtech boundaries. - Move Fast. Ship solutions multiple times a day, learn from results, and keep momentum. - Be Direct. Solve problems openly and collaborate across teams. - Thrive Together. Grow with a diverse, global team of people from over 40 different countries that learn from each other. - Have Fun. Celebrate wins, enjoy daily victories, and bring your energy. We welcome applications from people who will contribute to the diversity of our company.

Задачи: — искать специалистов на международном рынке: США, Канада, Австралия, UK, Европа — работать с Google / X-Ray Search, Boolean Search, профессиональными сообществами и базами — самостоятельно формировать поисковые запросы, target-листы компаний и стратегию поиска — анализировать эффективность каналов и outreach, тестировать новые подходы к сорсингу — работать с разными направлениями: FinTech, Payments, Product, AI / ML, SaaS, Consumer Tech, Business Требования: — опыт в роли Sourcer / Talent Sourcer / Researcher / Recruiter / Analyst от 1 года — уверенная работа с Boolean Search, желательно наличие прогретого аккаунта — хорошее владение Boolean Search и X-Ray Search — опыт cold sourcing — английский B2+ для работы с англоязычными профилями и письменной коммуникации Условия: — удаленная работа — график 5/2 — от 700$ + KPI + бонусы

Location: South Africa About the role We're a global education company running live, expert-led business courses across multiple markets. As we grow, so does the volume of legal questions that come with operating in many jurisdictions at once — how we contract with instructors in different countries, how we structure entities, how we respond when a regulator asks a question. We're hiring a dedicated legal role to take ownership of the research, analysis, and drafting that sits underneath those decisions. This is a genuinely broad role for someone early in their legal career who wants exposure to real cross-border commercial and employment questions, rather than a narrow slice of one. You'll research law in jurisdictions you haven't worked in before — the US, the UK and EU, South Africa, Australia, and across APAC — and your job will be to bring back a clear answer, not a hedge. What you'll do Research legal questions across multiple jurisdictions as we expand — contractor and partner engagement models, entity structuring, employment and commercial law, etc. Draft and maintain our contract templates: consulting agreements, teaching assistant agreements, statements of work, amendments, and termination agreements, with jurisdiction-specific variants Redline counterparty contracts and flag the terms that actually matter Build and own our legal register: active matters, deadlines, obligations, renewals, filings Scope and brief external counsel — write the question, assemble the pack, track cost and turnaround, and pressure-test what comes back Support entity formation, restructuring, and market-entry diligence Maintain approved communication templates and FAQs for teams who work with our instructors Build the systems that let a small legal function support a fast-growing company Requirements A law degree and 2–4 years of practical legal experience — private practice, in-house, or legal services Excellent written English. The core output of this role is a one-page memo a non-lawyer can act on immediately. Clarity beats comprehensiveness. Proven legal research skill, including in legal systems that aren't your own — and the judgment to know when a question needs local counsel and how to frame it for them Contract drafting and redlining experience Thoughtful, verified use of AI research tools. We use them; we also check every citation at source. Comfort with ambiguity, and the initiative to turn a half-formed business question into a precise legal one Interest in how the business actually works, not just the legal question in isolation Nice to have Experience with cross-border contractor or freelancer engagement models Employment or labour law background Admission to the bar in your home jurisdiction Data protection experience (GDPR, POPIA) Experience in a distributed, remote-first company Benefits Competitive Compensation: Competitive salary,Opportunities for career advancement as ELVTR continues to grow globally Learn and Grow: Free access to ELVTR courses,Ongoing professional development opportunities,Career growth within one of the world's fastest-growing online education companies Remote-First Culture : Work from wherever you're most productive, Flexible and supportive work environment,Collaborative international team Health & Wellbeing: Gym membership reimbursement,Mental health support, Generous paid vacation allowance Why Join ELVTR? Make an Impact: Every course you help create empowers professionals to build new skills, advance their careers, and unlock opportunities they never thought possible. Grow Your Career: We're committed to developing our people. As ELVTR continues to expand globally, you'll have opportunities to grow professionally, take on new challenges, and shape the future of online education. Join a Winning Team :Work alongside passionate educators, creators, marketers, and innovators who are committed to delivering world-class learning experiences and making education more accessible around the world. Ready to Help Shape the Future of Online Learning? Submit your CV and a short note on a legal question you researched where the answer wasn't obvious — what you found, and what you recommended.