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Location: Remote We are looking for a Trading Operations Specialist to support our algorithmic trading activities. Your main responsibility will be to ensure that trading runs smoothly, reliably, and safely, through careful execution of operational checks, real-time monitoring, and timely escalation. This is a hands-on role, not a management track - ideal for someone detail-oriented, disciplined, and motivated to work in a regulated algo-trading environment What You’ll Be Doing: Execute pre- and post-session checks to confirm system readiness and close out procedures Monitor intrasession invariants (positions, connectivity, latency, market data consistency, error rates) and promptly escalate deviations Follow escalation procedures to involve the right people at the right time when anomalies arise Contribute to continuous improvement of anomaly detection quality, incident reaction times, and communication efficiency Keep accurate operational records and logs for auditability and learning Shift-based schedule, ensuring reliable coverage across required trading hours. What We Look For In You: Bachelor’s degree in Finance, Economics, Mathematics, or related field (or equivalent practical experience) 3 years in trading operations, trade support, or market surveillance (experience in algo/electronic trading is a plus, but not required) Solid understanding of how financial markets and trading systems operate High attention to detail and ability to stay calm under pressure Comfortable following structured procedures while also spotting where they can be improved Clear communicator in English, able to escalate effectively and work with multidisciplinary teams Why Should You Join Our Team? Join an international team of highly qualified professionals Work remotely from an eligible location within the UTC−11 to UTC−5 time zone range. 40 paid days off Competitive salary

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. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: San Francisco, CA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. 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. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: Chicago DRW is a diversified trading firm with over 3 decades of experience bringing sophisticated technology and exceptional people together to operate in markets around the world. We value autonomy and the ability to quickly pivot to capture opportunities, so we operate using our own capital and trading at our own risk. Headquartered in Chicago with offices throughout the U.S., Canada, Europe, and Asia, we trade a variety of asset classes including Fixed Income, ETFs, Equities, FX, Commodities and Energy across all major global markets. We have also leveraged our expertise and technology to expand into three non-traditional strategies: real estate, venture capital and cryptoassets. We operate with respect, curiosity and open minds. The people who thrive here share our belief that it’s not just what we do that matters–it's how we do it. DRW is a place of high expectations, integrity, innovation and a willingness to challenge consensus. As a Research Engineer , you will be an integral member of a systematic trading team comprised of experienced technologists, quantitative researchers, and traders. Your team will work closely to solve challenging technological problems and contribute to our full tech stack, including software design, data engineering, distributed computing, and quantitative modeling. You will be surrounded by cutting edge technology, mentored by industry-leading engineers, offered training and continuing education opportunities, and given immediate responsibility.  We are looking for quantitatively minded people who are creative technologists, natural programmers, and disciplined engineers eager to develop new technologies that directly impact our business. How you will make an impact: Work with researchers to implement research studies, simulate trading strategies, and develop algorithms to compete in financial markets. Design trading strategy simulation software optimized for distributed computation Develop software for large scale data acquisition, storage, accessibility, and visualization Create user interfaces for data exploration and post trade analysis Accelerate the research lifecycle from strategy prototype to production deployment Evaluate new technology and improve our technology stack What you bring to the team: Bachelor’s degree in Computer Science, Computer Engineering, or related field Excellent software development skills in modern C++ and Python A strong understanding of object oriented design, data structures and algorithms A strong understanding of quantitative finance mathematics A solid foundation in programming with the ability to think, communicate, and code clearly A solid understanding of computer systems at every level of abstraction (hardware, OS, memory, network) Skills in multi‐threaded applications An understanding of how to build software for long term use and broad adoption Demonstrated ability to produce algorithmic code in a fast-paced environment The annual base salary range for this position is $175,000 to $225,000, depending on the candidate’s experience, qualifications, and relevant skill set. The position is also eligible for an annual discretionary bonus.  In addition, DRW offers a comprehensive suite of employee benefits including group medical, pharmacy, dental and vision insurance, 401k (with discretionary employer match), short and long-term disability, life and AD&D insurance, health savings accounts, and flexible spending accounts. For more information about DRW's processing activities and our use of job applicants' data, please view our Privacy Notice at https://drw.com/privacy-notice . California residents, please review the California Privacy Notice for information about certain legal rights at https://drw.com/california-privacy-notice . #LI-BL1

Location: London DRW is a diversified trading firm with over 3 decades of experience bringing sophisticated technology and exceptional people together to operate in markets around the world. We value autonomy and the ability to quickly pivot to capture opportunities, so we operate using our own capital and trading at our own risk. Headquartered in Chicago with offices throughout the U.S., Canada, Europe, and Asia, we trade a variety of asset classes including Fixed Income, ETFs, Equities, FX, Commodities and Energy across all major global markets. We have also leveraged our expertise and technology to expand into three non-traditional strategies: real estate, venture capital and cryptoassets. We operate with respect, curiosity and open minds. The people who thrive here share our belief that it’s not just what we do that matters–it's how we do it. DRW is a place of high expectations, integrity, innovation and a willingness to challenge consensus. As a Research Engineer , you will be an integral member of a systematic research team comprised of experienced technologists, quantitative researchers, and traders. Your team will work closely to solve challenging technological problems and contribute to our full tech stack, including software design, data engineering, distributed computing, and quantitative modeling. You will be surrounded by cutting edge technology, mentored by industry-leading engineers, offered training and continuing education opportunities, and given immediate responsibility.  We are looking for quantitatively minded people who are creative technologists, natural programmers, and disciplined engineers eager to develop new technologies that directly impact our business. How you will make an impact: Work with researchers to implement research studies, simulate trading strategies, and develop algorithms to compete in financial markets. Design trading strategy simulation software optimized for distributed computation Develop software for large scale data acquisition, storage, accessibility, and visualization Create user interfaces for data exploration and post trade analysis Accelerate the research lifecycle from strategy prototype to production deployment Evaluate new technology and improve our technology stack What you bring to the team: Bachelor’s degree in Computer Science, Computer Engineering, or related field Excellent software development skills in modern C++ and Python A strong understanding of object oriented design, data structures and algorithms A strong understanding of quantitative finance mathematics A solid foundation in programming with the ability to think, communicate, and code clearly A solid understanding of computer systems at every level of abstraction (hardware, OS, memory, network) Skills in multi‐threaded applications An understanding of how to build software for long term use and broad adoption Demonstrated ability to produce algorithmic code in a fast-paced environment For more information about DRW's processing activities and our use of job applicants' data, please view our Privacy Notice at https://drw.com/privacy-notice . California residents, please review the California Privacy Notice for information about certain legal rights at https://drw.com/california-privacy-notice . #LI-BL1

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; 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: 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.

Location: Remote About Us In partnership with SBI Group, we aim to bring the majority of Japanese equities on-chain, creating a secure, transparent, and high-performance trading infrastructure that can support institutional volumes while remaining accessible to retail participants. We are building a next-generation decentralized exchange with a fully on-chain order book. Our system is built with a custom state transition function and consensus layer, purpose-designed for high-performance, low-latency trading. The goal is to deliver a trustless platform that matches the speed and efficiency of traditional trading engines while providing full transparency by running execution as close as possible to the blockchain itself. Position Overview We are looking for a Senior Rust Engineer with strong expertise in system architecture and execution engines. You will be responsible for designing and implementing the CLOB execution layer, including the order book, matching engine, and blockchain client logic. This role is highly technical and requires end-to-end ownership of critical components, from architecture to optimization. While you’ll primarily collaborate with a remote team of experienced engineers, there will occasionally be opportunities to work onsite during offsite sessions to support onboarding and enable more efficient collaboration. Joining at this early stage of development offers a unique opportunity to influence critical technical decisions, achieve career growth, and enjoy competitive compensation. Key Responsibilities Architect and implement the on-chain order book and matching engine in Rust. Design and extend exchange-specific logic (order execution, risk checks, account/state management). Design and develop protocol-level components, such as state transition logic, consensus, validator interaction, and transaction processing pipelines. Implement integration with oracles, bridges, and external data providers, ensuring correctness and resilience in adversarial conditions. Optimize for low-latency execution, concurrency, and gas efficiency. Conduct benchmarking and stress testing to identify and address potential performance/throughput bottlenecks. Develop and maintain a comprehensive suite of unit, integration, and end-to-end tests to ensure code reliability and functionality. Requirements 5+ years of systems programming experience, with 3+ years in Rust. Proven track record building trading platforms, execution engines, or exchanges (DEX or centralized). Contributions to Rust-based L1 protocol projects (e.g., Solana, Cosmos SDK, Substrate). Deep understanding of distributed computing principles, including consensus algorithms, peer-to-peer (P2P) networking, and high-performance data structures. Deep knowledge of decentralized trading models (on-chain order books, AMMs, hybrid architectures). Ability to design and implement complex, production-grade systems independently. Big Bonus Experience with competitive programming or algorithmic problem solving. Expertise in low-latency design, concurrency, and performance optimization.

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 84 mobile network operators in 58 countries. We are looking for a 5G ZTE Engineer (both remote and 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, Keep time, performance and quality according to company requirements and customer contracts, Provide an optimization solution for NR & LTE and trace the solution to collaborate with operators to implement it, Design and plan wireless site for network with simulation tool (added advantage), New feature testing, technical discussion, and integration troubleshooting support. Job Requirements 10+ years of experience in radio planning & optimization, Minimum 3 years of experience on 5G ZTE and 5 years of 4G, Hands on ZTE vendor algorithm & tools, NetNumen, UME, NetMax, NGI, Capability of KPIs analysis and optimization, Complaints handling, drive test log files analysis, Familiar with radio planning tool and optimization tools, able to use the tools to work in high efficiency way.

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 84 mobile network operators in 58 countries. We are looking for a 5G Huawei Engineer (both remote and 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, Keep time, performance and quality according to company requirements and customer contracts, Provide an optimization solution for NR & LTE and trace the solution to collaborate with operators to implement it, Design and plan wireless site for network with simulation tool (added advantage), New feature testing, technical discussion, and integration troubleshooting support. Job Requirements 10+ years of experience in radio planning & optimization, Minimum 3 years of experience on 5G HUAWEI and 5 years of 4G, Hands on HUAWEI vendor algorithm & tools, iMaster, PRS, MAE, FMA, Capability of KPIs analysis and optimization, Complaints handling, drive test log files analysis, Familiar with radio planning tool and optimization tools, able to use the tools to work in high efficiency way.

Location: São Paulo, Brazil Workplace: remote At TechBiz Global , we are providing recruitment service to our TOP clients from our portfolio. We are currently looking for a skilled Sales executive to join one of our clients' teams. We are seeking a candidate with strong experience in financial services, wealth management, or fintech sales to build and grow the client base among HNWI and ultra-HNWI investors in São Paulo. The role involves business development, client relationship management, and execution of high-touch sales strategies to introduce client’s proprietary algorithmic trading models as premium investment solutions. Key Responsibilities Develop and execute a sales strategy to acquire and manage HNWI clients, family offices, and boutique wealth managers in São Paulo and broader Brazil. Promote client’s AI-driven algorithmic trading products as differentiated solutions for portfolio diversification, alpha generation, and risk management. Build and maintain long-term relationships with clients, ensuring high levels of satisfaction and retention. Conduct client presentations, portfolio demonstrations, and educational sessions to articulate the value of algorithmic trading. Collaborate with the marketing and product teams to customize offerings and improve client acquisition campaigns. Stay informed on local financial regulations, market trends, and competitive landscape to identify opportunities. Manage the end-to-end sales cycle, from lead generation to onboarding and after-sales client support. Meet and exceed quarterly revenue and client acquisition targets. Bachelor’s degree in Business, Finance, Economics, or related field (MBA/CFA a plus). 5+ years of experience in sales within private banking, wealth management, asset management, or fintech. Strong network and relationships with HNWI / family offices / investment advisors in São Paulo. Proven track record of meeting or exceeding sales targets in high-value financial products. Excellent presentation, negotiation, and relationship management skills. Knowledge of algorithmic trading, hedge funds, structured products, or alternative investments strongly preferred. Bilingual: Portuguese (native) and English (fluent). Spanish is a plus.

Location: London Who We Are: Galaxy Digital Inc. (Nasdaq: GLXY) is a global leader in digital assets and data center infrastructure, growing the economy that runs on code. Galaxy delivers the onchain infrastructure that connects institutions to digital assets, including trading, advisory, asset management, staking, self-custody, and tokenization. Galaxy also develops and operates data center infrastructure to power AI and HPC workloads. Anchored by its Helios campus in Texas, Galaxy is building a multi-gigawatt pipeline of more than 5.7 GW of potential capacity, positioning it among the largest and fastest-growing data center developers in North America. The Company is headquartered in New York City, with offices across North America, Europe, the Middle East, and Asia. Additional information about Galaxy's businesses and products is available on www.galaxy.com . What We Value: We are a diverse team of free thinkers, and fast movers united to help investors and creators energize the global economy. We are looking for individuals who thrive in a culture of builders and overachievers and embrace high performance, transparent feedback, and a mission-first approach. Our culture shapes our way of working and gets us where we want to be. Seek Excellence. Be Selective To Be Effective. Be Highly Aligned, Loosely Coupled. Disagree Transparently. Encourage Independent Decision-Making. Build Dream Teams. Who You Are: We’re seeking an experienced Algo Trading / Head of Execution to join our team. You have a proven track record of building and benchmarking execution algorithms. Ideally, you’ve been actively engaged with the crypto markets or have a strong curiosity about them. In this role, you will take the lead in developing greenfield algorithmic trading systems, shaping the core of our next-generation trading infrastructure. You’ll work closely with trading teams, stakeholders, and external partners to deliver critical initiatives that drive our business forward. If you’re a natural problem-solver with a passion for hands-on technical development in a global, fast-paced environment, we want to hear from you. What You’ll Do: Design and lead the development of a low-latency, high-throughput Algo Trading / Smart Order Router system Implement intelligent routing algorithms based on execution quality, liquidity, latency, and cost Collaborate with traders, and product managers to refine routing logic and build new algorithmic capabilities Integrate the SOR with the trading, booking and reporting stack Monitor and optimize system performance under real-world trading conditions Mentor junior developers, enforce code quality standards, and contribute to architectural decisions Provide support for production trading issues and continuously improve system resilience and failover mechanisms What We’re Looking For: 10+ years of experience developing routing strategies for specific markets (e.g., U.S. equities, EU markets, crypto exchanges) Knowledge of tick data analytics and real-time market data processing Familiarity with cloud-based market access or hybrid deployments Experience working in high-frequency or algorithmic trading environments Experience building low-latency systems and working with multicast/unicast market data feeds A solid understanding of the application stack and infrastructure associated with electronic and algorithmic trading Strong technical background, with the ability to understand system architecture and technical workflows Proficiency in FIX protocol and trading system architecture (OMS/EMS, market gateways) Familiarity with concurrency, networking, and memory management Experience with Linux systems and performance profiling tools A proactive, problem-solving mindset and the ability to thrive in a fast-paced, collaborative environment Bonus Points: Deep understanding of electronic trading, order types, and market microstructure (equities, options, FX, Crypto etc.) Experience in the DeFi, or crypto space Exposure to regulatory or compliance-driven environments Familiarity with cloud-based infrastructure (e.g., AWS, GCP) or DevOps processes What We Offer: Competitive base salary and discretionary bonus Company-paid health and protective benefits for employees and their eligible dependents Free virtual coaching and counseling sessions Opportunities to learn about the Crypto industry Smart, entrepreneurial, and fun colleagues Employee Resource Groups *Benefits may vary depending on location. Galaxy respects diversity and seeks to provide equal employment opportunities to all employees and job applicants for employment without regard to actual or perceived age, race, color, creed, religion, sex or gender (including pregnancy, childbirth, lactation and related medical conditions), gender identity or gender expression (including transgender status), sexual orientation, marital or partnership or caregiver status, ancestry, national origin, citizenship status, disability, military or veteran status, protected medical condition as defined by applicable state or local law, genetic information or predisposing genetic characteristic, or other characteristic protected by applicable federal, state, or local laws and ordinances. We will endeavor to make a reasonable accommodation to the known limitations of a qualified applicant with a disability unless the accommodation would impose an undue hardship on the operation of our business. If you believe you require such assistance to complete the application process or to participate in an interview, please contact careers@galaxy.com.