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We are seeking a Software Developer , preferably with successful competitive programming experience, to join our dynamic team. You will join a team of intelligent, calm, and thoughtful teammates with a strong focus on detail and a passion for streamlining business procedures. The solutions developed by the team have a profound impact on the entire business, so we expect you to have good soft skills and be responsible. The position is characterized by fast feedback loops and very tangible results of work. WHAT YOU’LL BE DOING: Implementation of efficient trading algorithms, finding a balance between performance of the solution and ease of maintenance Close communication with the Quantitative Research team regarding technical tasks Write a lot of asynchronous, template, network and thread-safe code WHAT WE LOOK FOR IN YOU: Strong knowledge of data structures, algorithms, and a competitive programmIng background Experience with C or C++ Understanding of Linux system internals and networking Decent level of written and spoken English to work in an international environment NICE-TO-HAVE: In-depth knowledge and expertise with low latency/real-time development with sub-microsecond latency LockFree containers and thinking pattern Knowledge of CUDA WHY SHOULD YOU JOIN OUR TEAM? Great challenges with fast feedback loops A welcoming group of highly qualified international professionals Cutting-edge hardware and technology Work remotely from anywhere in the world Access any of our global offices anytime Flexible schedule 40 paid days off Competitive salary

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 a TPU Kernel Engineer, you'll be responsible for identifying and addressing performance issues across many different ML systems, including research, training, and inference. A significant portion of this work will involve designing and optimizing kernels for the TPU. You will also provide feedback to researchers about how model changes impact performance. Strong candidates will have a track record of solving large-scale systems problems and low-level optimization. You may be a good fit if you: Have significant experience optimizing ML systems for TPUs, GPUs, or other accelerators Are results-oriented, with a bias towards flexibility and impact Pick up slack, even if it goes outside your job description Enjoy pair programming (we love to pair!) Want to learn more about machine learning research Care about the societal impacts of your work Strong candidates may also have experience with: High performance, large-scale ML systems Designing and implementing kernels for TPUs or other ML accelerators Understanding accelerators at a deep level, e.g. a background in computer architecture ML framework internals Language modeling with transformers Representative projects: Implement low-latency, high-throughput sampling for large language models Adapt existing models for low-precision inference Build quantitative models of system performance Design and implement custom collective communication algorithms Debug kernel performance at the assembly level 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

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: Our Inference team is responsible for building and maintaining the critical systems that serve Claude to millions of users worldwide. We bring Claude to life by serving our models via the industry's largest compute-agnostic inference deployments. We are responsible for the entire stack from intelligent request routing to fleet-wide orchestration across diverse AI accelerators. The team has a dual mandate: maximizing compute efficiency to serve our explosive customer growth, while enabling breakthrough research by giving our scientists the high-performance inference infrastructure they need to develop next-generation models. We tackle complex, distributed systems challenges across multiple accelerator families and emerging AI hardware running in multiple cloud platforms. Strong candidates may also have experience with: High-performance, large-scale distributed systems Implementing and deploying machine learning systems at scale Load balancing, request routing, or traffic management systems LLM inference optimization, batching, and caching strategies Kubernetes and cloud infrastructure (AWS, GCP) Python or Rust You may be a good fit if you: Have significant software engineering experience, particularly with distributed systems Are results-oriented, with a bias towards flexibility and impact Pick up slack, even if it goes outside your job description Want to learn more about machine learning systems and infrastructure Thrive in environments where technical excellence directly drives both business results and research breakthroughs Care about the societal impacts of your work Representative projects across the org: D

PLEASE NOTE: This is a fully remote, 1099 independent contractor opportunity with an estimated duration of six months and the potential for extension. To be eligible, candidates must be authorized to work in the United States; visa sponsorship is not available for this role. About the Program The Human Frontier Collective (HFC) Fellowship brings together top researchers and domain experts to collaborate on high-impact work that are shaping the future of AI. As an HFC Fellow, you’ll apply your academic and professional expertise to help design, evaluate, and interpret advanced generative AI systems—while gaining exposure to cutting-edge research and working alongside an interdisciplinary network of leading thinkers. What You'll Do Collaborative Work: Get invited to engage in high-impact projects with our partnered AI labs and platforms. Develop and evaluate complex financial scenarios to test and enhance AI accuracy in valuation, forecasting, and analysis; collaborate in interactive sessions to assess model outputs for market relevance and compliance; provide detailed feedback to improve AI capabilities; and contribute to specialized projects in financial modeling, risk assessment, and equity research. HFC Community: Beyond the work, you’ll become part of a supportive, interdisciplinary network of innovators and thought leaders committed to advancing frontier AI across domains. Contribute to Research Publications: Collaborate with Scale’s research team to co-author technical reports and research papers—boosting your academic visibility and professional recognition (e.g., SciPredict , PropensityBench , Professional Reasoning Benchmark ). Who Should Apply Education: PhD, Master, BBA in Finance, Economics, or related degrees. Certifications: CFA or CPA strongly preferred. Professional Background: 5+ years in FP&A, Investment Banking, Portfolio Management, Financial Consulting, or equivalent research experience. Skills: Strong proficiency in financial modeling,

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 Team Our team is organized around the north star goal of building an AI scientist – a system capable of solving the long term reasoning challenges and basic capabilities necessary to push the scientific frontier. Our team likes to think across the whole model stack. Currently the team is focused on improving models' abilities to use computers – as a laboratory for long horizon tasks and a key blocker to many scientific workflows. About the role As a Research Engineer on our team you will work end to end, identifying and addressing key blockers on the path to scientific AGI. Strong candidates should have familiarity with language model training, evaluation, and inference, be comfortable triaging research ideas and diagnosing problems and enjoy working collaboratively. Familiarity with performance optimization, distributed systems, vm/sandboxing/container deployment, and large scale data pipelines is highly encouraged. Join us in our mission to develop advanced AI systems that are both powerful and beneficial for humanity. Responsibilities: Working across the full stack to identify and remove bottlenecks preventing progress toward scientific AGI Develop approaches to address long-horizon task completion and complex reasoning challenges essential for scientific discovery Scaling research ideas from prototype to production Create benchmarks and evaluation frameworks to measure model capabilities in scientific workflows and computer use Implement distributed training systems and performance optimizations to support large-scale model development You may be a good fit if you: Have 8+ years of ML research experience Are

What We Do: Cybercrime is growing, and more businesses are getting hit by threats that used to target only the biggest organizations. That pushes defenders like us to operate at the highest level, and it deepens our need for good people who want to make a meaningful impact. Founded in 2015 by former NSA cyber operators, Huntress is a remote-first team working to make enterprise-grade cybersecurity accessible to businesses of all sizes. We work closely with security teams and service providers protecting complex environments, often without the time or headcount to handle it all. That’s why we build our technology in-house and back it with a 24/7 human-led Security Operations Center (SOC). As a result, our platform is never disconnected from the experts who manage it, ensuring our customers' protection. Huntress now secures more than 5M endpoints and 16M identities worldwide. Those numbers keep growing because more businesses rely on us to help carry the load and operate with more confidence. Every day, you can see that commitment in how we stand with our customers and how we show up for each other. Reports to: SDR Manager Location: Remote US Compensation Range: $58,500 base with on target earnings at $78,000 plus equity What You'll Do: Huntress is looking for a talented and passionate Sales Development Representative (SDR) to help fuel our continued growth. In this role, you will open doors for the Account Executive team by building relationships with managed service providers (MSPs) and managed security service providers (MSSPs), earning trust quickly, and turning early conversations into qualified meetings that move the pipeline forward. You are outcome-obsessed in how you work, with a clear eye on the right next step, the right partner fit, and the follow-through it takes to create real pipeline impact. In the daily rhythm of prospecting into the MSP and MSSP space, you bring warrior spirit. You stay steady through rejection, keep your standards high, and c

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: You want to build and run elegant and thorough machine learning experiments to help us understand and steer the behavior of powerful AI systems. You care about making AI helpful, honest, and harmless, and are interested in the ways that this could be challenging in the context of human-level capabilities. You could describe yourself as both a scientist and an engineer. As a Research Engineer on Alignment Science, you'll contribute to exploratory experimental research on AI safety, with a focus on risks from powerful future systems (like those we would designate as ASL-3 or ASL-4 under our Responsible Scaling Policy ), often in collaboration with other teams including Interpretability, Fine-Tuning, and the Frontier Red Team. Our blog provides an overview of topics that the Alignment Science team is either currently exploring or has previously explored. Our current topics of focus include... Scalable Oversight: Developing techniques to keep highly capable models helpful and honest, even as they surpass human-level intelligence in various domains. AI Control: Creating methods to ensure advanced AI systems remain safe and harmless in unfamiliar or adversarial scenarios. Alignment Stress-testing : Creating model organisms of misalignment to improve our empirical understanding of how alignment failures might arise. Automated Alignment Research: Building and aligning a system that can speed up & improve alignment research. Alignment Assessments : Understanding and documenting the highest-stakes and most concerning emerging properties of models through pre-deployment alignment and

Product Manager – Innovation & Design Location: Paris (Hybrid) | Practice Area: Technology & Engineering | Type: Permanent Imaginez et construisez des produits qui répondent aux vrais besoins des utilisateurs et transforment durablement les services financiers. Capco recherche des Product Managers pour accompagner les acteurs majeurs des services financiers et de l'énergie dans la conception de produits utiles à leurs clients et créateurs de valeur pour leur organisation. Au sein de notre capability Tech, Product & Engineering , vous intégrerez des équipes pluridisciplinaires réunissant Product Managers, ingénieurs, développeurs et experts métiers. Votre rôle sera de comprendre les besoins des utilisateurs, identifier les bonnes problématiques à résoudre et transformer ces insights en produits simples, viables et performants. Vous intégrerez également de manière pragmatique les outils d’IA et d’automatisation approuvés dans vos méthodes de travail pour accélérer la recherche, l’analyse et l’expérimentation, tout en conservant le jugement humain au cœur des décisions produit. Vos responsabilités Travailler avec des équipes produit pluridisciplinaires pour identifier les problématiques utilisateurs prioritaires et concevoir des solutions à la fois désirables, viables et techniquement réalisables. Intervenir sur l’ensemble du cycle de vie produit, de la discovery et de la recherche utilisateur jusqu’au lancement, à la mesure de la performance et à l’optimisation continue. Combiner études de marché, recherche qualitative, données quantitatives et comportements observés pour construire une compréhension structurée des utilisateurs et exploiter, lorsque pertinent, des outils d’IA approuvés pour accélérer l’analyse et faire émerger des insights. Intégrer les contraintes propres aux services financiers – réglementation, risques et contrôles, protection des données et viabilité économique – dans les décisions produit. Piloter le produit par l

By applying to this role, you will be considered for Research Engineer roles across all teams at OpenAI. About the Role As a Research Engineer here, you will be responsible for building AI systems that can perform previously impossible tasks or achieve unprecedented levels of performance. We're looking for people with solid engineering skills (for example designing, implementing, and improving a massive-scale distributed machine learning system), writing bug-free machine learning code, and building the science behind the algorithms employed. The most outstanding deep learning results are increasingly attained at a massive scale, and these results require engineers who are comfortable working in large distributed systems. We expect engineering to play a key role in most major advances in AI of the future. We expect you to: Have strong programming skills Have experience working in large distributed systems Be excited about OpenAI’s approach to research Nice to have: Interested in and thoughtful about the impacts of AI technology Past experience in creating high-performance implementations of deep learning algorithms About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment

By applying to this role, you will be considered for Research Scientist roles across all teams at OpenAI. About the Role As a Research Scientist here, you will develop innovative machine learning techniques and advance the research agenda of the team you work on, while also collaborating with peers across the organization. We are looking for people who want to discover simple, generalizable ideas that work well even at large scale, and form part of a broader research vision that unifies the entire company. We expect you to: Have a track record of coming up with new ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects Possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects Be excited about OpenAI’s approach to research Nice to have: Interested in and thoughtful about the impacts of AI technology Past experience in creating high-performance implementations of deep learning algorithms About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement . Background checks for

Qui sommes-nous? Artefact est un cabinet de conseil spécialisé en data et en intelligence artificielle, qui accompagne les entreprises pour transformer ces technologies en impact business concret et mesurable. A la croisée du conseil, de la data et de la technologie, nos 2 500 collaborateurs dans 27 pays mettent leurs expertises en commun pour concevoir, développer et déployer des solutions qui répondent aux enjeux de transformation de nos clients. Artefact est l'une des plus grandes agences internationales indépendantes pilotée par des experts media et data. Le département e-retail au sein d’Artefact accompagne des marques dans le développement de leur activité e-commerce sur les principaux e-retailers (ex Amazon) - d’un point de vue stratégique et opérationnel. Envie d'en savoir plus? Découvrez Artefact, nos expertises et notre culture : https://www.artefact.com Dans le cadre du développement de ce pôle, Artefact recherche un consultant Retail Media en stage pour Janvier 2027 . Missions : Le consultant Retail Media pilotera l’ensemble de ces actions : Participer à la définition de la stratégie retail media search et display en traduisant les objectifs du client, accompagnée des recommandations opérationnelles nécessaires. Appliquer directement la stratégie validée en mettant en œuvre les campagnes search et display programmatique sur les différentes e-retailers en France & à l’étranger (Amazon, C-Discount, Auchan, Carrefour etc.) Création de campagnes Mise en place de stratégies (enchères, audience…) Optimisations des campagnes Analyse et reporting des campagnes Être quotidiennement force de proposition et de conseil auprès du portefeuille clients qui vous est attribué Envoi de recommandations par mail Valorisation de l’expertise d’Artefact à travers des présentations (powerpoint, google slide) Échange avec les clients du pôle lors de réunions en visio ou en présentiel. Profil : De formation École de Commerce de préférence

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 Anthropic's production models undergo sophisticated post-training processes to enhance their capabilities, alignment, and safety. As a Research Engineer on our Post-Training team, you'll train our base models through the complete post-training stack to deliver the production Claude models that users interact with. You'll work at the intersection of cutting-edge research and production engineering, implementing, scaling, and improving post-training techniques like Constitutional AI, RLHF, and other alignment methodologies. Your work will directly impact the quality, safety, and capabilities of our production models. Note: For this role, we conduct all interviews in Python. This role may require responding to incidents on short-notice, including on weekends. Responsibilities: Implement and optimize post-training techniques at scale on frontier models Conduct research to develop and optimize post-training recipes that directly improve production model quality Design, build, and run robust, efficient pipelines for model fine-tuning and evaluation Develop tools to measure and improve model performance across various dimensions Collaborate with research teams to translate emerging techniques into production-ready implementations Debug complex issues in training pipelines and model behavior Help establish best practices for reliable, reproducible model post-training You may be a good fit if you: Thrive in controlled chaos and are energised, rather than overwhelmed, when juggling multiple urgent priorities Adapt quickly to changing priorities Maintain clarity when debugging complex, time-sensitive issues Have strong softwa

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 teams Our Reinforcement Learning teams lead Anthropic's reinforcement learning research and development, playing a critical role in advancing our AI systems. We've contributed to all Claude models, with significant impacts on the autonomy and coding capabilities of Claude Sonnet 4.5 and Opus 4.5. Our work spans several key areas: Developing systems that enable models to use computers effectively Advancing code generation through reinforcement learning Pioneering fundamental RL research for large language models Building scalable RL infrastructure and training methodologies Enhancing model reasoning capabilities We collaborate closely with Anthropic's alignment and frontier red teams to ensure our systems are both capable and safe. We partner with the applied production training team to bring research innovations into deployed models, and are dedicated to implement our research at scale. Our Reinforcement Learning teams sit at the intersection of cutting-edge research and engineering excellence, with a deep commitment to building high-quality, scalable systems that push the boundaries of what AI can accomplish. About the Role As a Research Engineer within Reinforcement Learning, you will collaborate with a diverse group of researchers and engineers to advance the capabilities and safety of large language models. This role blends research and engineering responsibilities, requiring you to both implement novel approaches and contribute to the research direction. You'll work on fundamental research in reinforcement learning, creating 'agentic' models via tool use for open-ended tasks such as computer use and autonomous software

About Us: Paytm is India's leading mobile payments and financial services distribution company. Pioneer of the mobile QR payments revolution in India, Paytm builds technologies that help small businesses with payments and commerce. Paytm’s mission is to serve half a billion Indians and bring them to the mainstream economy with the help of technology. Expectation: • Working closely with vertical product managers/ business leads to understand product use cases, customer journeys, business applicability and impact of each use case. • Ability to understand different technology platforms, their features and be able to work with solution architects/engineering leads and write detailed product requirement documents, manage future roadmaps and deliverables • Make sure that clear, simple, and technically sound decisions are made • With your strong domain knowledge of lending platforms, we expect you to provide your subject matter expertise in requirements solutioning • Ability to work with multiple stakeholders / senior management / cross-functional teams to influence them for quicker decisions, manage sudden technical roadblocks and be able to clear them • Lead product team processes (Agile/Scrum) and manage expectations and track roadmap regularly • Be involved in what your team is building - Run edge cases, test products proactively and its features to provide feedback early in the cycle, make sure entire journeys are covered, and that product reporting exists to track KPIs for the product and its success (data-driven product management). Superpowers that will help you succeed in this role: • Bachelor’s degree in engineering, computer science and/or related field • Professional experience in a product management or analytical role with hands on experience in banking processes • Having deep understanding of Lending and LMS (Loan Management System) Platform(s) in Product Management role building credit platform products Knowledge of Fintech/ BFSI/ Lending domain • Exp sh

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: You want to build and run elegant and thorough machine learning experiments to help us understand and steer the behavior of powerful AI systems. You care about making AI helpful, honest, and harmless, and are interested in the ways that this could be challenging in the context of human-level capabilities. You could describe yourself as both a scientist and an engineer. As a Research Engineer on Alignment Science, you'll contribute to exploratory experimental research on AI safety, with a focus on risks from powerful future systems (like those we would designate as ASL-3 or ASL-4 under our Responsible Scaling Policy ), often in collaboration with other teams including Interpretability, Fine-Tuning, and the Frontier Red Team. Our blog provides an overview of topics that the Alignment Science team is either currently exploring or has previously explored. For the London team, we are opportunistically hiring for the following research areas: AI Control: Creating methods to ensure advanced AI systems remain safe and harmless in unfamiliar or adversarial scenarios. Alignment Stress-testing : Creating model organisms of misalignment to improve our empirical understanding of how alignment failures might arise. Note: Currently, the team's hub is in San Francisco, so we require all candidates to be based at least 25% in London and travel to San Francisco occasionally. Additionally, we are prioritizing growing our San Francisco teams, so you may not hear back on your application to the London team unless we see an unusually strong fit. For this role, we conduct all interviews in Python. Representative