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Location: Baku Workplace: onsite RESPONSIBILITIES Develop and maintain new functionality; Design and implement new services to support product features; Proactively propose ideas for improving the product; Collaborate with engineers, product managers, designers, and QA to deliver end-to-end solutions; Own your code in production by monitoring, debugging, and continuously improving service performance and reliability; Write automated tests and follow CI/CD best practices to ensure high-quality deployments; Participate in code reviews, technical discussions, and knowledge sharing across teams. REQUIREMENTS Experience in programming and backend development of industrial web applications using PHP and/or Golang; Strong understanding of algorithms and data structures; Understanding of decomposition principles, OOP, and design patterns; Ability to write testable code, including unit and functional tests; Good command of SQL, database design, and OLTP/OLAP approaches; Ability to participate effectively in team-based development; English proficiency at B2 level. NICE TO HAVE Experience in building high-load enterprise applications and event-driven systems; Knowledge of application architecture patterns and experience applying them; Experience working with continuous integration and deployment systems (Docker, Jenkins, GitLab, etc.); Experience with frontend development using any framework, preferably React. The duties and responsibilities of this position may evolve over time to support the organization’s goals and individual growth. This job description is intended to outline the general nature and level of work being performed and is not intended to be an exhaustive list of all duties, responsibilities, and qualifications required. By submitting your application, you consent to Xsolla conducting background checks, where permitted by law, after the final interview stage. All checks will comply with local regulations, and your information will be handled confidentially. Xsolla takes your privacy seriously and will not sell or externally distribute any personal data received during the hiring process. In accordance with applicable data protection laws, Xsolla is committed to protecting your personal information and respecting your privacy. For any inquiries related to data privacy, please contact: careers@xsolla.com Explore more opportunities at: https://xsolla.com/careers

Location: San Jose, California, United States Who We Are At OKX, we believe that the future will be reshaped by crypto, and ultimately contribute to every individual's freedom. OKX is a leading crypto exchange, and the developer of OKX Wallet, giving millions access to crypto trading and decentralized crypto applications (dApps). OKX is also a trusted brand by hundreds of large institutions seeking access to crypto markets. We are safe and reliable, backed by our Proof of Reserves. Across our multiple offices globally, we are united by our core principles: We Before Me , Do the Right Thing , and Get Things Done . These shared values drive our culture, shape our processes, and foster a friendly, rewarding, and diverse environment for every OK-er. About the Opportunity: The Sr Data Scientist, Risk will offer a strategic perspective, deep analytical and modeling capabilities, and a collaborative working style. The right candidate will have strong intellectual curiosity and passion for achieving business results. An ability to quickly define the problem, research and leverage state-of-the-art modeling techniques, and provide timely recommendations will be essential. Key skills will include a strong analytical mindset, deep understanding of most popular machine learning algorithms and lead key initiatives with integrity and a passion for investigations, problem solving, and troubleshooting. What You’ll Be Doing : Identify complex fraud patterns and their technical root causes through detailed data mining and analysis, including identification of sophisticated fraud methods employed by actors who are deliberately trying to avoid detection. Serve as technical SME by sharing new data mining techniques, maintaining technical reference documentation, and interfacing with partner technology teams. Collaborate across business and technology stakeholders to communicate analytical findings to both technical and non-technical audiences. Provide technical guidance for engineering projects that incorporate new data points into the investigation team’s toolkit, such as API integrations or internal data transformations. Link Analysis/Graph analytics to find and mitigate deeply-connected fraud networks and detect new accounts being added to these networks Unsupervised learning methods to augment existing supervised models, or detect portfolio anomalies Development of machine learning models Partner with product and engineering team in implementing features and models, and enhancing systems What We Look For In You: Master’s degree (or PhD) in Statistics, Mathematics, Operations Research, Computer Science, Economics, Engineering or other quantitative discipline. Bachelor’s degree with significant relevant experience will be considered. 4+ years of fraud analytics experience in financial services or FinTechs Crypto/Blockchain experience Deep understanding of modern machine learning techniques / algorithms including GBM, XGBoost, LGBM, etc. Advanced programming skills of statistical / analytical software (SQL, R, Python,etc.); Successful track record of owning and driving large, complex data analysis projects. Demonstrated capacity for innovation and outside-the-box thinking in the creation of new capabilities and processes that are unstructured or exploratory in nature. Experience in a fast-paced startup environment with a strong level of initiative; and Ability and willingness to travel as needed. Strong communicator in both writing and speaking Multi-tasking and strong project management skills Nice to Haves: Hands-on experience/knowledge of modeling in machine learning (GBM, XGBoost, Random Forest, etc.); and Perks & Benefits Competitive total compensation package L&D programs and Education subsidy for employees' growth and development Various team building programs and company events Wellness and meal allowances Comprehensive healthcare schemes for employees and dependants More that we love to tell you along the process! OKX Statement: The salary range for this position is $223,661.00 to $268,333.00 . The salary offered depends on a variety of factors, including job-related knowledge, skills, experience, and market location. In addition to the salary, a performance bonus and long-term incentives may be provided as part of the compensation package, as well as a full range of medical, financial, and/or other benefits, dependent on the position offered. Applicants should apply via Okcoin and OKX internal or external careers site. OKX is committed to equal employment opportunities regardless of race, color, genetic information, creed, religion, sex, sexual orientation, gender identity, lawful alien status, national origin, age, marital status, and non-job related physical or mental disability, or protected veteran status. Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. #LI-HYBRID #LI-ED1 Notice: All official OKX vacancies are published on this website. While roles may appear on selected third-party platforms from time to time, information on other sites may be inaccurate or outdated. If in doubt, please apply directly through our official careers website. Information collected and processed as part of the recruitment process of any job application you choose to submit is subject to OKX 's Candidate Privacy Notice .

Location: Montreal; Canada Workplace: remote ABOUT YOU   We are looking for Backend Engineers who are innovative, collaborative, and adaptable to join our engineering team. The best candidate will be someone who thrives in a fast-paced, highly collaborative, and dynamic environment and drive best practices in software development.   Strong technical expertise, analytical skills, and communication abilities are essential, along with experience in software development and design across various technologies and frameworks.   If you’re passionate about advancing technology solutions, designing scalable and maintainable systems, and love partnering with diverse teams to create innovative and impactful solutions, we would love to hear from you!   ABOUT US   Xsolla is a global commerce company with robust tools and services to help developers solve the inherent challenges of the video game industry. From indie to AAA, companies partner with Xsolla to help them fund, distribute, market, and monetize their games. Grounded in the belief in the future of video games, Xsolla is resolute in the mission to bring opportunities together, and continually make new resources available to creators. Headquartered and incorporated in Los Angeles, California, Xsolla operates as the merchant of record and has helped over 1,500+ game developers to reach more players and grow their businesses around the world. With more paths to profits and ways to win, developers have all the things needed to enjoy the game. For more information, visit xsolla.com. Responsibilities: Develop new functionality and maintain it Create new services for new features Offer new ideas for improving the product Qualifications & Skills: Have experience in programming and industrial web application backend development in PHP and/or Golang Have a good understanding of algorithms and data structures Understand decomposition principles, OOP and patterns Can write testable code, unit and functional tests Have a good command of SQL, database design, OLTP/OLAP approaches Participate in team development Benefits:We are passionate about fostering a supportive environment for our team, so we prioritize the physical, mental, and emotional well-being of our employees and their families through a comprehensive Benefits Program. This includes medical, dental, and vision, PTO, and a personalized career roadmap for each employee. By investing in professional development through training and educational opportunities, we ensure that our team thrives both personally and professionally. Together, we’re not just building a business; we’re cultivating a community that values creativity, collaboration, and the transformative power of play.    Equal Employment Opportunity Statement: Xsolla is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate based on race, color, religion, sex, national origin, age, disability, sexual orientation, gender identity, or any other characteristic protected by law. We consider qualified applicants with criminal histories in accordance with the Fair Chance Act.   Criminal History Consideration: For the Backend Engineer, we will conduct a background check that may include the following: Criminal history check Employment verification Education verification   Relevance to Job Responsibilities: The background check is relevant to this position because of the following role responsibilities: Accessing confidential company data Ensuring compliance with regulatory requirements   Rights Under the Fair Chance Act: Applicants are encouraged to inquire about their rights under the Fair Chance Act. If you have questions regarding our hiring practices, please contact careers@xsolla.com. The listed range is specific to Canada and varies based on factors such as location and experience.

Location: Berlin, Germany Fin , now part of Salesforce, is on a mission to help businesses provide perfect customer experiences. Our AI Agent Fin is the highest-performing AI Customer Agent on the market today, enabling businesses to deliver impeccable, always-on customer support across the customer journey, from service, to sales, to ecommerce. Powered by our own AI models, Fin resolves complex customer issues end-to-end across every channel, with minimal set-up and integration. Fin can also be combined with our natively integrated Intercom help desk, giving modern support teams one single system. Together with Salesforce, the #1 AI CRM, where humans with agents drive customer success, we're building the future of customer experience. Here, ambition meets action. Tech meets trust. And innovation isn't a buzzword, it's a way of life. The world of work as we know it is changing, and we're looking for Trailblazers who are passionate about bettering business and the world through AI. Ready to level up your career at the company leading workforce transformation in the agentic era? You're in the right place. Agentforce is the future of AI, and you are the future of Salesforce. What's the opportunity? We’re looking for Staff Product Engineers to join the AI Group to build Fin's AI-powered products. Product Engineers working in ML work closely with both our ML Scientists and product teams. They must deeply understand our product, our customers, our ML tech stack and our broader product stack. Our group is responsible for defining new ML features, researching appropriate algorithms and technologies, and rapidly getting first prototypes in our customers’ hands. We are an extremely product focussed team. We work in partnership with Product and Design functions of teams we support. Our team's dedicated Engineers enable us to move to production fast, often shipping to beta in weeks after a successful offline test. We are very passionate about applying machine learning technology, and have productized everything from classic supervised models, to cutting-edge unsupervised clustering algorithms, to novel applications of transformer neural networks. We test and measure the real customer impact of each model we deploy. If you are an experienced product engineer who takes an analytical approach to development and has some hands-on experience with ML systems, we'd love to hear from you! What will I be doing? Product Engineers in the AI Group Build the systems that power Fin's flagship AI products. This usually means working in our ML Python tech stack, but at times also means working across the product on our Rails app too. Work alongside our ML Scientists bring proof-of-concept code to production; ensuring it’s robust and scalable for real-world use. Partner with product teams outside of our group, to shape the best AI-powered product experience for our customers.. Contribute to all phases of software development including ideation, prototyping, and implementation and testing. Play an active role in the hiring, mentoring, and career development of other engineers. Raise the bar for technical standards, performance, reliability, and operational excellence within the group and across Fin. Profile we’re looking for These are meant to be indicative, not hard requirements. 10+ years of experience shipping high-quality products. No ML experience required. We believe you can be highly effective immediately by bringing excellent software engineering skills, and learn ML as you work on the team. You can demonstrate significant impact in the work that you have done. You take pride in having strong technical fundamentals; you love learning and are willing to work hard to invest in your development. Deep knowledge of a high-level programming language (for example, Ruby, Python, Javascript etc.) but it doesn’t need to be a language that we use here! Strong willingness to fight for good outcomes Bias towards progress over perfection BSc in Computer Science, Maths or Statistics or related discipline Bonus skills & attributes Previous experience in data analytics, or statistical role #LI-Hybrid Unleash Your Potential When you join Salesforce, you’ll be limitless in all areas of your life. Our benefits and resources support you to find balance and be your best, and our AI agents accelerate your impact so you can do your best. Together, we’ll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love. Apply today to not only shape the future — but to redefine what’s possible — for yourself, for AI, and the world. In the United States, compensation offered will be determined by factors such as location, job level, job-related knowledge, skills, and experience. Certain roles may be eligible for incentive compensation, equity, and benefits. At Fin, we want to give people what they need to do the best work of their careers. Our benefits and programs are designed to support your health and wellbeing, your family, your time away from work, and your financial future. Offerings vary by location in line with local practices and requirements. Learn more about working at Fin and the benefits we offer at fin.ai/careers . Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Salesforce will consider for employment qualified applicants with arrest and conviction records. Policies Fin has a hybrid working policy. We believe that working in person helps us stay connected, collaborate easier and create a great culture while still providing flexibility to work from home. We expect employees to be in the office at least three days per week. We have a radically open and accepting culture at Fin. We avoid spending time on divisive subjects to foster a safe and cohesive work environment for everyone. As an organization, our policy is to not advocate on behalf of the company or our employees on any social or political topics out of our internal or external communications. We respect personal opinion and expression on these topics on personal social platforms on personal time, and do not challenge or confront anyone for their views on non-work related topics. Our goal is to focus on doing incredible work to achieve our goals and unite the company through our core values . Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that’s inclusive, and free from discrimination. Know your rights: workplace discrimination is illegal. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications – without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education.

Location: London, England Fin , now part of Salesforce, is on a mission to help businesses provide perfect customer experiences. Our AI Agent Fin is the highest-performing AI Customer Agent on the market today, enabling businesses to deliver impeccable, always-on customer support across the customer journey, from service, to sales, to ecommerce. Powered by our own AI models, Fin resolves complex customer issues end-to-end across every channel, with minimal set-up and integration. Fin can also be combined with our natively integrated Intercom help desk, giving modern support teams one single system. Together with Salesforce, the #1 AI CRM, where humans with agents drive customer success, we're building the future of customer experience. Here, ambition meets action. Tech meets trust. And innovation isn't a buzzword, it's a way of life. The world of work as we know it is changing, and we're looking for Trailblazers who are passionate about bettering business and the world through AI. Ready to level up your career at the company leading workforce transformation in the agentic era? You're in the right place. Agentforce is the future of AI, and you are the future of Salesforce. What's the opportunity? We’re looking for Staff Product Engineers to join the AI Group to build Fin's AI-powered products. Product Engineers working in ML work closely with both our ML Scientists and product teams. They must deeply understand our product, our customers, our ML tech stack and our broader product stack. Our group is responsible for defining new ML features, researching appropriate algorithms and technologies, and rapidly getting first prototypes in our customers’ hands. We are an extremely product focussed team. We work in partnership with Product and Design functions of teams we support. Our team's dedicated Engineers enable us to move to production fast, often shipping to beta in weeks after a successful offline test. We are very passionate about applying machine learning technology, and have productized everything from classic supervised models, to cutting-edge unsupervised clustering algorithms, to novel applications of transformer neural networks. We test and measure the real customer impact of each model we deploy. If you are an experienced product engineer who takes an analytical approach to development and has some hands-on experience with ML systems, we'd love to hear from you! What will I be doing? Product Engineers in the AI Group Build the systems that power Fin's flagship AI products. This usually means working in our ML Python tech stack, but at times also means working across the product on our Rails app too. Work alongside our ML Scientists bring proof-of-concept code to production; ensuring it’s robust and scalable for real-world use. Partner with product teams outside of our group, to shape the best AI-powered product experience for our customers.. Contribute to all phases of software development including ideation, prototyping, and implementation and testing. Play an active role in the hiring, mentoring, and career development of other engineers. Raise the bar for technical standards, performance, reliability, and operational excellence within the group and across Fin. Profile we’re looking for These are meant to be indicative, not hard requirements. 10+ years of experience shipping high-quality products. No ML experience required. We believe you can be highly effective immediately by bringing excellent software engineering skills, and learn ML as you work on the team. You can demonstrate significant impact in the work that you have done. You take pride in having strong technical fundamentals; you love learning and are willing to work hard to invest in your development. Deep knowledge of a high-level programming language (for example, Ruby, Python, Javascript etc.) but it doesn’t need to be a language that we use here! Strong willingness to fight for good outcomes Bias towards progress over perfection BSc in Computer Science, Maths or Statistics or related discipline Bonus skills & attributes Previous experience in data analytics, or statistical role #LI-Hybrid Unleash Your Potential When you join Salesforce, you’ll be limitless in all areas of your life. Our benefits and resources support you to find balance and be your best, and our AI agents accelerate your impact so you can do your best. Together, we’ll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love. Apply today to not only shape the future — but to redefine what’s possible — for yourself, for AI, and the world. In the United States, compensation offered will be determined by factors such as location, job level, job-related knowledge, skills, and experience. Certain roles may be eligible for incentive compensation, equity, and benefits. At Fin, we want to give people what they need to do the best work of their careers. Our benefits and programs are designed to support your health and wellbeing, your family, your time away from work, and your financial future. Offerings vary by location in line with local practices and requirements. Learn more about working at Fin and the benefits we offer at fin.ai/careers . Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Salesforce will consider for employment qualified applicants with arrest and conviction records. Policies Fin has a hybrid working policy. We believe that working in person helps us stay connected, collaborate easier and create a great culture while still providing flexibility to work from home. We expect employees to be in the office at least three days per week. We have a radically open and accepting culture at Fin. We avoid spending time on divisive subjects to foster a safe and cohesive work environment for everyone. As an organization, our policy is to not advocate on behalf of the company or our employees on any social or political topics out of our internal or external communications. We respect personal opinion and expression on these topics on personal social platforms on personal time, and do not challenge or confront anyone for their views on non-work related topics. Our goal is to focus on doing incredible work to achieve our goals and unite the company through our core values . Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that’s inclusive, and free from discrimination. Know your rights: workplace discrimination is illegal. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications – without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education.

Location: Dublin, Ireland Fin , now part of Salesforce, is on a mission to help businesses provide perfect customer experiences. Our AI Agent Fin is the highest-performing AI Customer Agent on the market today, enabling businesses to deliver impeccable, always-on customer support across the customer journey, from service, to sales, to ecommerce. Powered by our own AI models, Fin resolves complex customer issues end-to-end across every channel, with minimal set-up and integration. Fin can also be combined with our natively integrated Intercom help desk, giving modern support teams one single system. Together with Salesforce, the #1 AI CRM, where humans with agents drive customer success, we're building the future of customer experience. Here, ambition meets action. Tech meets trust. And innovation isn't a buzzword, it's a way of life. The world of work as we know it is changing, and we're looking for Trailblazers who are passionate about bettering business and the world through AI. Ready to level up your career at the company leading workforce transformation in the agentic era? You're in the right place. Agentforce is the future of AI, and you are the future of Salesforce. What's the opportunity? We’re looking for Staff Product Engineers to join the AI Group to build Fin's AI-powered products. Product Engineers working in ML work closely with both our ML Scientists and product teams. They must deeply understand our product, our customers, our ML tech stack and our broader product stack. Our group is responsible for defining new ML features, researching appropriate algorithms and technologies, and rapidly getting first prototypes in our customers’ hands. We are an extremely product focussed team. We work in partnership with Product and Design functions of teams we support. Our team's dedicated Engineers enable us to move to production fast, often shipping to beta in weeks after a successful offline test. We are very passionate about applying machine learning technology, and have productized everything from classic supervised models, to cutting-edge unsupervised clustering algorithms, to novel applications of transformer neural networks. We test and measure the real customer impact of each model we deploy. If you are an experienced product engineer who takes an analytical approach to development and has some hands-on experience with ML systems, we'd love to hear from you! What will I be doing? Product Engineers in the AI Group Build the systems that power Fin's flagship AI products. This usually means working in our ML Python tech stack, but at times also means working across the product on our Rails app too. Work alongside our ML Scientists bring proof-of-concept code to production; ensuring it’s robust and scalable for real-world use. Partner with product teams outside of our group, to shape the best AI-powered product experience for our customers.. Contribute to all phases of software development including ideation, prototyping, and implementation and testing. Play an active role in the hiring, mentoring, and career development of other engineers. Raise the bar for technical standards, performance, reliability, and operational excellence within the group and across Fin. Profile we’re looking for These are meant to be indicative, not hard requirements. 10+ years of experience shipping high-quality products. No ML experience required. We believe you can be highly effective immediately by bringing excellent software engineering skills, and learn ML as you work on the team. You can demonstrate significant impact in the work that you have done. You take pride in having strong technical fundamentals; you love learning and are willing to work hard to invest in your development. Deep knowledge of a high-level programming language (for example, Ruby, Python, Javascript etc.) but it doesn’t need to be a language that we use here! Strong willingness to fight for good outcomes Bias towards progress over perfection BSc in Computer Science, Maths or Statistics or related discipline Bonus skills & attributes Previous experience in data analytics, or statistical role #LI-Hybrid Unleash Your Potential When you join Salesforce, you’ll be limitless in all areas of your life. Our benefits and resources support you to find balance and be your best, and our AI agents accelerate your impact so you can do your best. Together, we’ll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love. Apply today to not only shape the future — but to redefine what’s possible — for yourself, for AI, and the world. In the United States, compensation offered will be determined by factors such as location, job level, job-related knowledge, skills, and experience. Certain roles may be eligible for incentive compensation, equity, and benefits. At Fin, we want to give people what they need to do the best work of their careers. Our benefits and programs are designed to support your health and wellbeing, your family, your time away from work, and your financial future. Offerings vary by location in line with local practices and requirements. Learn more about working at Fin and the benefits we offer at fin.ai/careers . Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Salesforce will consider for employment qualified applicants with arrest and conviction records. Policies Fin has a hybrid working policy. We believe that working in person helps us stay connected, collaborate easier and create a great culture while still providing flexibility to work from home. We expect employees to be in the office at least three days per week. We have a radically open and accepting culture at Fin. We avoid spending time on divisive subjects to foster a safe and cohesive work environment for everyone. As an organization, our policy is to not advocate on behalf of the company or our employees on any social or political topics out of our internal or external communications. We respect personal opinion and expression on these topics on personal social platforms on personal time, and do not challenge or confront anyone for their views on non-work related topics. Our goal is to focus on doing incredible work to achieve our goals and unite the company through our core values . Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that’s inclusive, and free from discrimination. Know your rights: workplace discrimination is illegal. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications – without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education.

Location: Istanbul, Turkey P.I. Works is the first company in the world to automate the management of a commercial 5G network. Our automated network management products and services empower Mobile Operators to accelerate network transformation and to drive network quality and efficiency on the path to 5G. These solutions have been deployed across 85 mobile network operators in 58 countries. We are looking for a 5G Huawei / Ericsson Engineer (only onsite positions are available) to join our team. Job Responsibilities Perform network optimization and network audit to meet customer requirements Provide 5G deployment and optimization strategy support (Layer management and traffic steering strategy, NSA/SA, spectrum strategy, site densification, network sharing, TDD RN optimization, DSS, network slicing, spectral efficiency) for customers Focus on executing audit and optimization of services, where you will be accountable for part of the solution and of the service process Ensure acceptance (site, cluster) criteria are met by controlling acceptance reports from OEM vendors Provide an optimization solution for NR & LTE and trace the solution to collaborate with operators to implement it New feature testing, technical discussion, and integration troubleshooting support Organize training sessions related to 5G technology and optimization Design and plan wireless site for network with simulation tool (added advantage Job Requirements 8+ years of experience in radio planning & optimization Minimum 2 years of experience on 5G Huawei / Ericsson and 4+ years of 4G Huawei / Ericsson. 5G rollout experience is a plus Hands on HUAWEI vendor algorithm & tools, iMaster, PRS, MAE, FMA or on ERICSSON vendor algorithm & tools ENM CLI (Command Line Interface) , ENM Shell Terminal, WinFIOL, Alarm Monitor , Alarm Overview, PM Initation and Collection Capability of KPIs analysis and optimization, customer complaint handling, drive test log files analysis Experience with TEMS Discovery and Actix (capability of postprocessing DT logs by using DT analysis tools such as TEMS Discovery and/or Actix and provide recommendations to improve DT KPIs) Familiar with radio planning tool and optimization tools, able to use the tools to work in high efficiency way Turkish language is a plus

Location: New York; San Francisco; Toronto; Montreal Workplace: Remote WHO ARE WE? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Role Overview: Large Language Models (LLMs) continue to push the boundaries of what AI systems can do — but inference is still the bottleneck. The Model Efficiency team is responsible for pushing the limits of LLM inference efficiency across our foundation models. We explore and ship breakthroughs across the model execution stack, including: - model architecture and MoE routing optimization - decoding and inference-time algorithm improvements - software/hardware co-design for GPU acceleration - performance optimization without compromising model quality Please Note: We have offices in Toronto, Montreal, San Francisco, New York, Paris, Seoul and London. We embrace a remote-friendly environment, and as part of this approach, we strategically distribute teams based on interests, expertise, and time zones to promote collaboration and flexibility. You'll find the Model Efficiency team concentrated in the EST and PST time zones, these are our preferred locations. Key Responsibilities: As a Staff Research Engineer, you will develop, prototype, and deploy techniques that materially improve how fast and efficiently our models run in production. Qualifications: - Have a PhD in Machine Learning or a related field - Understand LLM architecture, and how to optimize LLM inference given resource constraints - Have significant experience with one or more techniques that enhance model efficiency - Strong software engineering skills - An appetite to work in a fast-paced high-ambiguity start-up environment - Publications at top-tier conferences and venues (ICLR, ACL, NeurIPS) - Passion to mentor others Working Location: This role can be based remotely or from one of our office locations listed on the job description - there is no minimum in-office qualification requirement. We care most about hiring exceptional people regardless of locations, though please check the location listed on the posting for guidance around the core time zone or working hours alignment expected for the role.   FULL-TIME EMPLOYEES AT COHERE ENJOY THESE PERKS: - A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch. - Full health and dental benefits, including a separate budget for mental health. - RRSP matching, 401K, Pension Scheme. - 100% Parental Leave top-up for up to 6 months, for either parent. - Annual enrichment benefits: Arts & culture, fitness/wellness, quality time, and a workspace improvement credit. Education & learning stipend for conferences, courses, and coaching. - 6 weeks of paid vacation (30 working days!) - Budget for traveling to other offices if you are remote, plus an annual company offsite. HOW AND WHERE WE WORK: - Cohere is remote-friendly, but we also have offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul with more opening soon. - For those in the office: a daily lunch program, plenty of snacks, and regular community and social events. - For those not near an office: a co-working benefit so you can work alongside others in your city. - Everyone receives a $500 home office stipend to set up your workspace properly. If any of the above doesn’t line up exactly with your experience, we still encourage you to apply. We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form https://docs.google.com/forms/d/12a6IrLdF3kI2nonKSr4tiFuz18rLQbaeYV-JM9L4o9Q/edit, and we will work together to meet your needs. We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider. Beware of Scams: Cohere will never ask for payment or third-party services (e.g., CV writing) as part of our hiring process. All legitimate roles are listed on the Cohere careers page and LinkedIn only, with all communications from Cohere employees coming from an @cohere.com or @cw.cohere email alias. If jobs are viewed on other sites then please verify these through our official careers https://cohere.com/careers page.

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: When you see what modern language models are capable of, do you wonder, "How do these things work? How can we trust them?" The Interpretability team at Anthropic is working to reverse-engineer how trained models work because we believe that a mechanistic understanding is the most robust way to make advanced systems safe. We’re looking for researchers and engineers to join our efforts. People mean many different things by "interpretability". We're focused on mechanistic interpretability, which aims to discover how neural network parameters map to meaningful algorithms. Some useful analogies might be to think of us as trying to do "biology" or "neuroscience" of neural networks using “microscopes” we build, or as treating neural networks as binary computer programs we're trying to "reverse engineer". A few places to learn more about our work and team at a high level are this introduction to Interpretability from our research lead, Chris Olah ; a discussion of our work on the Hard Fork podcast produced by the New York Times, and this blog post (and accompanying video) sharing more about some of the engineering challenges we’d had to solve to get these results. Some of our team's notable publications include A Mathematical Framework for Transformer Circuits , In-context Learning and Induction Heads , Toy Models of Superposition , Scaling Monosemanticity , and our Circuits’ Methods and Biology papers. This work builds on ideas from members' work prior to Anthropic such as the original circuits thread , Multimodal Neurons , Activation Atlases , and Building Blocks . We aim to create a solid foundation for mechanistically understanding neural networks and making them safe (see our vision post ). In the short term, we have focused on resolving the issue of "superposition" (see Toy Models of Superposition , Superposition, Memorization, and Double Descent , and our May 2023 update ), which causes the computational units of the models, like neurons and attention heads, to be individually uninterpretable, and on finding ways to decompose models into more interpretable components. Our subsequent work found millions of features in Sonnet, one of our production language models, represents progress in this direction. In our most recent work, we develop methods that allow us to build circuits using features and use this circuits to understand the mechanisms associated with a model's computation and study specific examples of multi-hop reasoning, planning, and chain-of-thought faithfulness on Haiku 3.5, one of our production models.” This is a stepping stone towards our overall goal of mechanistically understanding neural networks. We often collaborate with teams across Anthropic, such as Alignment Science and Societal Impacts to use our work to make Anthropic’s models safer. We also have an Interpretability Architectures project that involves collaborating with Pretraining. Responsibilities: Develop methods for understanding LLMs by reverse engineering algorithms learned in their weights Design and run robust experiments, both quickly in toy scenarios and at scale in large models Create and analyze new interpretability features and circuits to better understand how models work. Build infrastructure for running experiments and visualizing results Work with colleagues to communicate results internally and publicly You may be a good fit if you: Have a strong track record of scientific research (in any field), and have done some work on Interpretability Enjoy team science – working collaboratively to make big discoveries Are comfortable with messy experimental science. We're inventing the field as we work, and the first textbook is years away You view research and engineering as two sides of the same coin. Every team member writes code, designs and runs experiments, and interprets results You can clearly articulate and discuss the motivations behind your work, and teach us about what you've learned. You like writing up and communicating your results, even when they're null To learn more about the skills we look for and how to prepare for this role, see our blog post – So You Want to Work in Mechanistic Interpretability? Familiarity with Python is required for this role. Role Specific Location Policy: This role is based in San Francisco office; however, we are open to considering exceptional candidates for remote work on a case-by-case basis. 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: $350,000 — $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. 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. Note: we don't have open Research Manager positions on the Interpretability team at this time. However, we're actively growing our team of Research Engineers and Research Scientists . If you're excited about interpretability research and open to an individual contributor role, we encourage you to apply. About the Interpretability team When you see what modern language models are capable of, do you wonder, "How do these things work? How can we trust them?" The Interpretability team’s mission is to reverse engineer how trained models work, and Interpretability research is one of Anthropic’s core research bets on AI safety. We believe that a mechanistic understanding is the most robust way to make advanced systems safe. People mean many different things by "interpretability". We're focused on mechanistic interpretability, which aims to discover how neural network parameters map to meaningful algorithms. Some useful analogies might be to think of us as trying to do "biology" or "neuroscience" of neural networks, or as treating neural networks as binary computer programs we're trying to "reverse engineer". We aim to create a solid scientific foundation for mechanistically understanding neural networks and making them safe (see our vision post ). We have focused on resolving the issue of "superposition" (see Toy Models of Superposition , Superposition, Memorization, and Double Descent , and our May 2023 update ), which causes the computational units of the models, like neurons and attention heads, to be individually uninterpretable, and on finding ways to decompose models into more interpretable components. Our subsequent work which found millions of features in Claude 3.0 Sonnet, one of our production language models, represents progress in this direction. In our most recent work , we developed methods that allow us to build circuits using features and use these circuits to understand the mechanisms associated with a model's computation and study specific examples of multi-hop reasoning, planning, and chain-of-thought faithfulness on Claude Haiku 3.5, one of our production models.” This is a stepping stone towards our overall goal of mechanistically understanding neural networks. A few places to learn more about our work and team are this introduction to Interpretability from our research lead, Chris Olah, Stanford CS25 lecture given by Josh Batson, and TWIML AI podcast with Emmanuel Ameisen. Some of our team's notable publications include and our Circuits’ Methods and Biology papers, Scaling Monosemanticity: Extracting Interpretable Features from Claude 3 Sonnet , Towards Monosemanticity: Decomposing Language Models With Dictionary Learning , A Mathematical Framework for Transformer Circuits , In-context Learning and Induction Heads , and Toy Models of Superposition . This work builds on ideas from members' work prior to Anthropic such as the original circuits thread , Multimodal Neurons , Activation Atlases , and Building Blocks . About the role As a manager on the Interpretability team, you'll support a team of expert researchers and engineers who are trying to understand at a deep, mechanistic level, how modern large language models work internally. Few things can accelerate this work more than great managers. Your work as manager will be critical in making sure that our fast-growing team is able to meet its ambitious safety research goals over the coming years. In this role, you will partner closely with an individual contributor research lead to drive the team's success, translating cutting-edge research ideas into tangible goals and overseeing their execution. You will manage team execution, careers and performance, facilitate relationships within and across teams, and drive the hiring pipeline. If you're more interested in making individual direct technical contributions to our research as the primary focus of your role, feel free to apply to our Research Scientist or Research Engineer roles instead. Key responsibilities Partner with a research lead on direction, project planning and execution, hiring, and people development Set and maintain a high bar for execution speed and quality, including identifying improvements to processes that help the team operate effectively Coach and support team members to have more impact and develop in their careers Drive the team's recruiting efforts, including hiring planning, process improvements, and sourcing and closing Help identify and support opportunities for collaboration with other teams across Anthropic Communicate team updates and results to other teams and leadership Maintain a deep understanding of the team's technical work and its implications for AI safety You may be a good fit if you Are an experienced manager (minimum 2-5 years) with a track record of effectively leading highly technical research and/or engineering teams Have a background in machine learning, AI, or a related technical field Actively enjoy people management and are experienced with coaching and mentorship, performance evaluation, career development, and hiring for technical roles Have strong project management skills, including prioritization and cross-functional coordination and collaboration Have managed technical teams through periods of ambiguity and change Are a quick learner, capable of understanding and contributing to discussions on complex technical topics and are motivated to learn about our research Are a strong communicator both in speaking and in writing Believe that advanced AI systems could have a transformative effect on the world, and are passionate about helping make sure that transformation goes well Strong candidates may also have Experience scaling engineering infrastructure Experience working on open-ended, exploratory research agendas aimed at foundational insights Some familiarity with our work and mechanistic interpretability Role-Specific Location Policy This role is expected to be in our SF office for 3 days a week. 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: $350,000 — $500,000 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. 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: Berlin, Germany Fin , now part of Salesforce, is on a mission to help businesses provide perfect customer experiences. Our AI Agent Fin is the highest-performing AI Customer Agent on the market today, enabling businesses to deliver impeccable, always-on customer support across the customer journey, from service, to sales, to ecommerce. Powered by our own AI models, Fin resolves complex customer issues end-to-end across every channel, with minimal set-up and integration. Fin can also be combined with our natively integrated Intercom help desk, giving modern support teams one single system. Together with Salesforce, the #1 AI CRM, where humans with agents drive customer success, we're building the future of customer experience. Here, ambition meets action. Tech meets trust. And innovation isn't a buzzword, it's a way of life. The world of work as we know it is changing, and we're looking for Trailblazers who are passionate about bettering business and the world through AI. Ready to level up your career at the company leading workforce transformation in the agentic era? You're in the right place. Agentforce is the future of AI, and you are the future of Salesforce. Speed is something we fight for every day at Fin, and we believe Berlin is built for people who share that instinct. We are drawn to Berlin by its rare blend of deep technical talent and rich creative culture – all within a vibrant, globally connected city that’s close to our R&D hubs in Dublin and London. It’s a place where the best of the best technical talent thrive, and where people from around the world are eager to relocate and build ambitious products. Our ambition is to hire 100 people in Berlin over the year ahead across engineering, AI, data science, product, and design. We believe this is the most exciting time to join, be the founding R&D talent in the region and make a lasting impact as we build the world's number one customer agent! What's the opportunity? Fin's Machine Learning team is responsible for defining new ML features, researching appropriate algorithms and technologies, and rapidly getting first prototypes in our customers’ hands. We are an extremely product focussed team. We work in partnership with Product and Design functions of teams we support. Our team's dedicated ML product engineers enable us to move to production fast, often shipping to beta in weeks after a successful offline test. We are very passionate about applying machine learning technology, and have productized everything from classic supervised models, to cutting-edge unsupervised clustering algorithms, to novel applications of transformer neural networks. We test and measure the real customer impact of each model we deploy. What will I be doing? Identify areas where ML can create value for our customers Identify the right ML framing of product problems Working with teammates and Product and Design stakeholders Conduct exploratory data analysis and research Deeply understand the problem area Research and identify the right algorithms and tools Being pragmatic, but innovating right to the cutting-edge when needed Perform offline evaluation to gather evidence an algorithm will work Work with engineers to bring prototypes to production Plan, measure & socialize learnings to inform iteration Partner deeply with the rest of team, and others, to build excellent ML products What skills might I need? Broad applied machine learning knowledge 3-5 years applied ML experience Practical stats knowledge (experiment design, dealing with confounding etc) Intermediate programming skills Strong communication skills, both within engineering teams and across disciplines. Comfort with ambiguity Typically have advanced education in ML or related field (e.g. MSc) Scientific thinking skills Bonus skills & attributes Track record shipping ML products PhD or other experience in a research environment Deep experience in an applicable ML area. E.g. NLP, Deep learning, Bayesian methods, Reinforcement learning, clustering Strong stats or math background Visualization, data skills, SQL, matplotlib, etc. Benefits We are a well treated bunch, with awesome benefits! If there’s something important to you that’s not on this list, talk to us! Competitive salary, annual bonus and equity Regular compensation reviews - we reward great work! Generous paid time off above statutory minimum Generous family leave (maternity, paternity), to let you spend valuable time with your loved ones Hybrid working MacBooks are our standard, but we also offer Windows for certain roles when needed. Unlimited access to Claude Code and best-in-class AI tools; experimentation & building is encouraged & celebrated Fun events for employees, friends, and family! Unleash Your Potential When you join Salesforce, you’ll be limitless in all areas of your life. Our benefits and resources support you to find balance and be your best, and our AI agents accelerate your impact so you can do your best. Together, we’ll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love. Apply today to not only shape the future — but to redefine what’s possible — for yourself, for AI, and the world. In the United States, compensation offered will be determined by factors such as location, job level, job-related knowledge, skills, and experience. Certain roles may be eligible for incentive compensation, equity, and benefits. At Fin, we want to give people what they need to do the best work of their careers. Our benefits and programs are designed to support your health and wellbeing, your family, your time away from work, and your financial future. Offerings vary by location in line with local practices and requirements. Learn more about working at Fin and the benefits we offer at fin.ai/careers . Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Salesforce will consider for employment qualified applicants with arrest and conviction records. Policies Fin has a hybrid working policy. We believe that working in person helps us stay connected, collaborate easier and create a great culture while still providing flexibility to work from home. We expect employees to be in the office at least three days per week. We have a radically open and accepting culture at Fin. We avoid spending time on divisive subjects to foster a safe and cohesive work environment for everyone. As an organization, our policy is to not advocate on behalf of the company or our employees on any social or political topics out of our internal or external communications. We respect personal opinion and expression on these topics on personal social platforms on personal time, and do not challenge or confront anyone for their views on non-work related topics. Our goal is to focus on doing incredible work to achieve our goals and unite the company through our core values . Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that’s inclusive, and free from discrimination. Know your rights: workplace discrimination is illegal. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications – without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education.

Location: Tallinn, Estonia; Helsinki, Finland; Abu Dhabi, United Arab Emirates; Dubai, United Arab Emirates; Sharjah, United Arab Emirates Workplace: on-site At TechBiz Global , we are providing recruitment service to our TOP clients from our portfolio. We are currently seeking a Senior Protocol Engineer to join one of our clients' teams . If you're looking for an exciting opportunity to grow in a innovative environment, this could be the perfect fit for you. You’ll be leading the design and development of next-generation consensus models, building secure and scalable EVM systems, and mentoring a world-class engineering team. What You’ll Do Lead the development of EVM-based systems and blockchain infrastructure. Design and implement Proof of Stake and other consensus models . Build and optimize smart contract platforms and tooling . Collaborate with leadership to define technical strategy and roadmap. Mentor engineers, fostering a culture of innovation and excellence. Drive decentralization and scalability improvements. 10+ years of experience in blockchain protocols, distributed systems, or AI infrastructure. 7 to 8 years hands-on expertise with consensus algorithms and cryptography . Proven track record in blockchain protocol design . Strong background in software engineering (Rust, Go, Solidity, JavaScript, Ruby, etc.). 10 years of experience in leading technical teams in blockchain/crypto companies . Contributions to open-source blockchain projects . A reputation as an innovator in blockchain/crypto . Nice-to-Have Experience in multi-coin pools or algorithmic optimization. Familiarity with NEAR, Blackcoin, Ethereum, BitHalo, or similar ecosystems . Why Join Us? This is a chance to work with a passionate team, shape the future of decentralized technologies, and build solutions that will define the next era of blockchain.

Location: London, England Fin , now part of Salesforce, is on a mission to help businesses provide perfect customer experiences. Our AI Agent Fin is the highest-performing AI Customer Agent on the market today, enabling businesses to deliver impeccable, always-on customer support across the customer journey, from service, to sales, to ecommerce. Powered by our own AI models, Fin resolves complex customer issues end-to-end across every channel, with minimal set-up and integration. Fin can also be combined with our natively integrated Intercom help desk, giving modern support teams one single system. Together with Salesforce, the #1 AI CRM, where humans with agents drive customer success, we're building the future of customer experience. Here, ambition meets action. Tech meets trust. And innovation isn't a buzzword, it's a way of life. The world of work as we know it is changing, and we're looking for Trailblazers who are passionate about bettering business and the world through AI. Ready to level up your career at the company leading workforce transformation in the agentic era? You're in the right place. Agentforce is the future of AI, and you are the future of Salesforce. What's the opportunity? Fin's Machine Learning team is responsible for defining new ML features, researching appropriate algorithms and technologies, and rapidly getting first prototypes in our customers’ hands. We are an extremely product focussed team. We work in partnership with Product and Design functions of teams we support. Our team's dedicated ML product engineers enable us to move to production fast, often shipping to beta in weeks after a successful offline test. We are very passionate about applying machine learning technology, and have productized everything from classic supervised models, to cutting-edge unsupervised clustering algorithms, to novel applications of transformer neural networks. We test and measure the real customer impact of each model we deploy. What will I be doing? Play an active role in hiring, mentoring and career development of other engineers Raise the bar for technical standards, performance, reliability, and operational excellence Identify areas where ML can create value for our customers Identify the right ML framing of product problems - Working with teammates and Product and Design stakeholders Conduct exploratory data analysis and research - Deeply understand the problem area Research and identify the right algorithms and tools - Being pragmatic, but innovating right to the cutting-edge when needed Perform offline evaluation to gather evidence an algorithm will work Work with engineers to bring prototypes to production Plan, measure & socialize learnings to inform iteration Partner deeply with the rest of team, and others, to build excellent ML products What skills might I need? 5-8 years applied ML experience Previous background in a senior/staff role (data science, software development or academic) Significant, demonstrated impact that your work has had on the product and/or the teams Strong programming skills Experience as the primary technical leader for a team Strong communication skills, both within engineering teams and across disciplines. Comfort with ambiguity Typically have advanced education in ML or related field (e.g. MSc) Scientific thinking skills Bonus skills & attributes Track record shipping ML products PhD or other experience in a research environment Deep experience in an applicable ML area - E.g. NLP, Deep learning, Bayesian methods, Reinforcement learning, clustering Strong stats or math background Visualization, data skills, SQL, matplotlib, etc. Unleash Your Potential When you join Salesforce, you’ll be limitless in all areas of your life. Our benefits and resources support you to find balance and be your best, and our AI agents accelerate your impact so you can do your best. Together, we’ll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love. Apply today to not only shape the future — but to redefine what’s possible — for yourself, for AI, and the world. In the United States, compensation offered will be determined by factors such as location, job level, job-related knowledge, skills, and experience. Certain roles may be eligible for incentive compensation, equity, and benefits. At Fin, we want to give people what they need to do the best work of their careers. Our benefits and programs are designed to support your health and wellbeing, your family, your time away from work, and your financial future. Offerings vary by location in line with local practices and requirements. Learn more about working at Fin and the benefits we offer at fin.ai/careers . Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Salesforce will consider for employment qualified applicants with arrest and conviction records. Policies Fin has a hybrid working policy. We believe that working in person helps us stay connected, collaborate easier and create a great culture while still providing flexibility to work from home. We expect employees to be in the office at least three days per week. We have a radically open and accepting culture at Fin. We avoid spending time on divisive subjects to foster a safe and cohesive work environment for everyone. As an organization, our policy is to not advocate on behalf of the company or our employees on any social or political topics out of our internal or external communications. We respect personal opinion and expression on these topics on personal social platforms on personal time, and do not challenge or confront anyone for their views on non-work related topics. Our goal is to focus on doing incredible work to achieve our goals and unite the company through our core values . Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that’s inclusive, and free from discrimination. Know your rights: workplace discrimination is illegal. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications – without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education.

Location: London, England Fin , now part of Salesforce, is on a mission to help businesses provide perfect customer experiences. Our AI Agent Fin is the highest-performing AI Customer Agent on the market today, enabling businesses to deliver impeccable, always-on customer support across the customer journey, from service, to sales, to ecommerce. Powered by our own AI models, Fin resolves complex customer issues end-to-end across every channel, with minimal set-up and integration. Fin can also be combined with our natively integrated Intercom help desk, giving modern support teams one single system. Together with Salesforce, the #1 AI CRM, where humans with agents drive customer success, we're building the future of customer experience. Here, ambition meets action. Tech meets trust. And innovation isn't a buzzword, it's a way of life. The world of work as we know it is changing, and we're looking for Trailblazers who are passionate about bettering business and the world through AI. Ready to level up your career at the company leading workforce transformation in the agentic era? You're in the right place. Agentforce is the future of AI, and you are the future of Salesforce. What's the opportunity? Fin's Machine Learning team is responsible for defining new ML features, researching appropriate algorithms and technologies, and rapidly getting first prototypes in our customers’ hands. We are an extremely product focussed team. We work in partnership with Product and Design functions of teams we support. Our team's dedicated ML product engineers enable us to move to production fast, often shipping to beta in weeks after a successful offline test. We are very passionate about applying machine learning technology, and have productized everything from classic supervised models, to cutting-edge unsupervised clustering algorithms, to novel applications of transformer neural networks. We test and measure the real customer impact of each model we deploy. What will I be doing? Identify areas where ML can create value for our customers Identify the right ML framing of product problems Working with teammates and Product and Design stakeholders Conduct exploratory data analysis and research Deeply understand the problem area Research and identify the right algorithms and tools Being pragmatic, but innovating right to the cutting-edge when needed Perform offline evaluation to gather evidence an algorithm will work Work with engineers to bring prototypes to production Plan, measure & socialize learnings to inform iteration Partner deeply with the rest of team, and others, to build excellent ML products What skills might I need? Broad applied machine learning knowledge 3-5 years applied ML experience Practical stats knowledge (experiment design, dealing with confounding etc) Intermediate programming skills Strong communication skills, both within engineering teams and across disciplines. Comfort with ambiguity Typically have advanced education in ML or related field (e.g. MSc) Scientific thinking skills Bonus skills & attributes Track record shipping ML products PhD or other experience in a research environment Deep experience in an applicable ML area. E.g. NLP, Deep learning, Bayesian methods, Reinforcement learning, clustering Strong stats or math background Visualization, data skills, SQL, matplotlib, etc. Unleash Your Potential When you join Salesforce, you’ll be limitless in all areas of your life. Our benefits and resources support you to find balance and be your best, and our AI agents accelerate your impact so you can do your best. Together, we’ll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love. Apply today to not only shape the future — but to redefine what’s possible — for yourself, for AI, and the world. In the United States, compensation offered will be determined by factors such as location, job level, job-related knowledge, skills, and experience. Certain roles may be eligible for incentive compensation, equity, and benefits. At Fin, we want to give people what they need to do the best work of their careers. Our benefits and programs are designed to support your health and wellbeing, your family, your time away from work, and your financial future. Offerings vary by location in line with local practices and requirements. Learn more about working at Fin and the benefits we offer at fin.ai/careers . Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Salesforce will consider for employment qualified applicants with arrest and conviction records. Policies Fin has a hybrid working policy. We believe that working in person helps us stay connected, collaborate easier and create a great culture while still providing flexibility to work from home. We expect employees to be in the office at least three days per week. We have a radically open and accepting culture at Fin. We avoid spending time on divisive subjects to foster a safe and cohesive work environment for everyone. As an organization, our policy is to not advocate on behalf of the company or our employees on any social or political topics out of our internal or external communications. We respect personal opinion and expression on these topics on personal social platforms on personal time, and do not challenge or confront anyone for their views on non-work related topics. Our goal is to focus on doing incredible work to achieve our goals and unite the company through our core values . Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that’s inclusive, and free from discrimination. Know your rights: workplace discrimination is illegal. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications – without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education.

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: Pioneering the next generation of AI requires breakthrough innovations in GPU performance and systems engineering. As a GPU Performance Engineer, you'll architect and implement the foundational systems that power Claude and push the frontiers of what's possible with large language models. You'll be responsible for maximizing GPU utilization and performance at unprecedented scale, developing cutting-edge optimizations that directly enable new model capabilities and dramatically improve inference efficiency. Working at the intersection of hardware and software, you'll implement state-of-the-art techniques from custom kernel development to distributed system architectures. Your work will span the entire stack—from low-level tensor core optimizations to orchestrating thousands of GPUs in perfect synchronization. Strong candidates will have a track record of delivering transformative GPU performance improvements in production ML systems and will be excited to shape the future of AI infrastructure alongside world-class researchers and engineers. You might be a good fit if you: Have deep experience with GPU programming and optimization at scale Are impact-driven, passionate about delivering measurable performance breakthroughs Can navigate complex systems from hardware interfaces to high-level ML frameworks Enjoy collaborative problem-solving and pair programming Want to work on state-of-the-art language models with real-world impact Care about the societal impacts of your work Thrive in ambiguous environments where you define the path forward Strong candidates may also have experience with: GPU Kernel Development: CUDA, Triton, CUTLASS, Flash Attention, tensor core optimization ML Compilers & Frameworks: PyTorch/JAX internals, torch.compile, XLA, custom operators Performance Engineering: Kernel fusion, memory bandwidth optimization, profiling with Nsight Distributed Systems: NCCL, NVLink, collective communication, model parallelism Low-Precision: INT8/FP8 quantization, mixed-precision techniques Production Systems: Large-scale training infrastructure, fault tolerance, cluster orchestration Representative projects: Co-design attention mechanisms and algorithms for next-generation hardware architectures Develop custom kernels for emerging quantization formats and mixed-precision techniques Design distributed communication strategies for multi-node GPU clusters Optimize end-to-end training and inference pipelines for frontier language models Build performance modeling frameworks to predict and optimize GPU utilization Implement kernel fusion strategies to minimize memory bandwidth bottlenecks Create resilient systems for planet-scale distributed training infrastructure Profile and eliminate performance bottlenecks in production serving infrastructure Partner with hardware vendors to influence future accelerator capabilities and software stacks Deadline to apply: None. Applications will be reviewed on a rolling basis. The expected salary range for this position is: 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: $280,000 — $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. 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; Palo Alto; New York City Perplexity is looking for an Applied AI Engineer to design, build, and iterate on cutting-edge agents powering our core experience in Perplexity Computer. Working in this mission critical team, you will develop frontier context layer applications - fulfilling the curiosity of millions of users across the globe. Key Responsibilities - Apply state-of-the-art ML and LLM techniques to solve problems spanning: - Personalization (LLM memory, context summarization, retrieval and ranking); - Contextual recommendations and Monetization applications - Build frontier agent capabilities on top of Perplexity Computer - Build auto research harness for both offline and online techniques, designing experiments and metrics that provide deep insight into quality and impact. - Own the entire model lifecycle from research to production: data analysis, modeling, evaluation, offline/online A/B testing, and iterative improvement and build autonomous harness for agent squad to explore different problem spaces. - Collaborate cross-functionally with engineers, PMs, data scientists, and designers to ensure our AI drives meaningful product improvements. - Stay at the forefront of ML/AI innovation by evaluating and incorporating emerging research and algorithms into the product lifecycle. Preferred Qualifications - 5+ years experience building and shipping robust AI products for large-scale, user-facing or data-driven products. - Strong software engineering skills (Python, production-quality codebases, collaborative development) and experience using agentic coding tools for large scale parallel developments. - In-depth experience with the full AI lifecycle: data analysis, rigorous evaluation, and ongoing monitoring/improvement. - Proven collaborator and communicator; excels in high-velocity, cross-functional teams. - Curious, driven by end-user/product impact, and passionate about advancing the state of applied ML and AI. - BS, MS, or PhD in Computer Science, Engineering, or related field (or equivalent experience). Bonus Points For - Experience with LLM context engineering or harness engineering. - Experience in mid-training or post-training frontier open source models - Experience in large scale user-centric and content-centric personalization challenges (user modeling, retrieval, content ranking, etc).

Location: Berlin (Germany) At thinkcell, we’re seeking bright, creative C++ Developers with a solid theoretical background. Whether you're a seasoned professional or a recent graduate in Computer Science, Physics, or Mathematics, what matters most is your problem-solving ability and C++ skills. At thinkcell, we combine deep technical challenges with a healthy work-life balance and a culture that values thoughtful engineering over rushed delivery. Most of our team is based in Berlin, but we also welcome remote developers working from UTC–1 to UTC+4, reflecting our commitment to flexibility and collaboration across regions. Ideal candidates have: Strong C++ programming skills (through education or experience) A background in Computer Science, Mathematics, or Physics A passion for elegant, efficient algorithms Ability to work independently and creative problem-solving approaches Good command of English (German not required) How You’ll Work You’ll collaborate closely with the team, without being stuck in recurring meetings. Your feature ships when you think it’s ready - no time pressure! We encourage contributions from anyone What We Offer Brilliant Team: Work with international colleagues with strong academic and professional experience Work–life balance: Flexible working hours and an environment that respects your time and focus. Stable Environment: Join a market leader with a reliable product. Competitive salary & Relocation Support to Berlin Guaranteed raise to 130k EUR after the first year Our Values As part of our team, you will embody and help shape the following principles that define us: Forward Thinking : We embrace change and challenge the status quo. Ownership : We take pride in our work and learn from our mistakes. Customer First : We prioritize delivering lasting value. Unified Team : We foster collaboration, respect, and integrity. Strive for Excellence : We set ambitious goals and pursue quality. Why is thinkcell the right place for you? We empower over 1.3 million users across 35,000 companies, including top consulting firms and major global enterprises. With offices in Berlin, Munich, Denver, Boston, London, Tokyo, and Dubai, we’re a diverse team of over 220 people, committed to innovation and excellence. thinkcell is more than a job – it's a chance to be part of an innovative, inclusive team that values collaboration and growth. We encourage applicants from all backgrounds to apply. Together, we can shape the future of productivity software. We can’t wait to see what you’ll bring to the team!

Location: London; Europe; New York; Paris; Toronto Workplace: Hybrid WHO ARE WE? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Role overview: Code-generating LLMs and autonomous agents are revolutionizing how software is built and tasks are automated. At Cohere, we’re pushing the boundaries of what’s possible with these technologies for enterprises, and we’re looking for a senior member for the Agent Code team. You’ll be at the forefront of research and engineering, driving the development of cutting-edge code LLMs and agent systems that can interact with the digital world to solve complex tasks with minimal human oversight. This role is hands-on and research-driven. You’ll dive into the latest literature on code LLMs and agents, experiment with frontier models, and collaborate with a team of talented engineers and researchers to build scalable, production-ready solutions. At Cohere, we blend engineering and research seamlessly—everyone contributes to both, depending on their interests and organizational needs. We provide access to world-class compute resources, data, and talent to ensure you can do your best work. Note: We have offices in London, Toronto, New York and San Francisco, but we’re also remote-friendly! This team operates primarily between ET to CET time zones, so we’re seeking candidates in locations that align with these hours for effective collaboration. Key responsibilities: - Stay up-to-date with the latest research in code LLMs, agents, and related fields, implementing novel ideas into our systems. - Design and implement scalable strategies to train code models, and deploy agent frameworks for inference and sampling. You will be collaborating with the pretraining team, create SFT trajectories and work on existing and new RL algorithms - Hillclimb on existing benchmarks and design new ones that reflect the needs of our enterprise users - Lead experiments on our state-of-the-art compute infrastructure, pushing the boundaries of what’s possible with frontier LLMs. Qualifications: - A PhD in Computer Science, Machine Learning, or a related field, with publications in top-tier venues (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP). - Deep expertise in code LLMs and agent systems, with a strong understanding of the latest research and trends. We are looking for people who not only have worked with code models, but have actively contributed to their development - Hands-on experience with frontier LLMs and their applications in code generation or automation. - Strong software engineering skills, with proficiency in Python and PyTorch, TensorFlow, or similar frameworks. - Experience with distributed systems, cloud infrastructure, and scalable architectures. - A proactive, self-motivated mindset, with a passion for solving ambitious, open-ended problems. Working Location: This role can be based remotely or from one of our office locations listed on the job description - there is no minimum in-office qualification requirement. We care most about hiring exceptional people regardless of locations, though please check the location listed on the posting for guidance around the core time zone or working hours alignment expected for the role. FULL-TIME EMPLOYEES AT COHERE ENJOY THESE PERKS: - A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch. - Full health and dental benefits, including a separate budget for mental health. - RRSP matching, 401K, Pension Scheme. - 100% Parental Leave top-up for up to 6 months, for either parent. - Annual enrichment benefits: Arts & culture, fitness/wellness, quality time, and a workspace improvement credit. Education & learning stipend for conferences, courses, and coaching. - 6 weeks of paid vacation (30 working days!) - Budget for traveling to other offices if you are remote, plus an annual company offsite. HOW AND WHERE WE WORK: - Cohere is remote-friendly, but we also have offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul with more opening soon. - For those in the office: a daily lunch program, plenty of snacks, and regular community and social events. - For those not near an office: a co-working benefit so you can work alongside others in your city. - Everyone receives a $500 home office stipend to set up your workspace properly. If any of the above doesn’t line up exactly with your experience, we still encourage you to apply. We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form https://docs.google.com/forms/d/12a6IrLdF3kI2nonKSr4tiFuz18rLQbaeYV-JM9L4o9Q/edit, and we will work together to meet your needs. We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider. Beware of Scams: Cohere will never ask for payment or third-party services (e.g., CV writing) as part of our hiring process. All legitimate roles are listed on the Cohere careers page and LinkedIn only, with all communications from Cohere employees coming from an @cohere.com or @cw.cohere email alias. If jobs are viewed on other sites then please verify these through our official careers https://cohere.com/careers page.