Thought Machine jobs

Senior Machine Learning & AI Engineer Bristol posted: Posted Today

AI Machine Learning Engineer 4 Locations posted: Posted Today

Senior AI Engineer London (hybrid)

Senior AI Research Scientist Remote - Germany posted: Posted Yesterday

Member of Technical Staff, Platform San Francisco, CA, San Francisco, California, United States, New York, NY TL;DR: Listen teaches AI what people actually think and want. We're Sequoia-backed, raised $100M, and our customers include Anthropic, Google, and Cursor. We're hiring engineers who can build a complex AI-native product on a small team of former founders and top-tier builders. Background As AI gets better at building things, the bottleneck shifts to knowing what to build. We're the bridge between AI systems and what humans actually want. Today our customers are companies. Soon, AIs themselves will be our customers. Our platform runs AI-moderated video interviews at massive scale. We find the right people from a network of millions, our AI conducts open-ended conversations with thousands of them in parallel, and we surface what to build next. What used to take research teams weeks per study, we do in hours. Where it's going: every interview feeds a human preference model. We simulate human behavior at scale: how people react to new ideas, how they make decisions, how preferences shape markets, and how change ripples through society. We expose this as the Human API. An AI agent writes code, asks Listen whether users would actually want a feature, gets a grounded answer back, and iterates. Closed-loop product development at AI speed. Every coding agent will eventually need this signal. Company highlights - Series B with $100M raised from Sequoia, Conviction, Ribbit, AI Grant, and Pear VC. - Selective team of - Customers include Anthropic,

Tech Lead Manager, Vision & AI San Francisco, CA | Hybrid | Remote ABOUT THE ROLE Voxel's perception system is the technical core of everything we ship. Our models detect human activity, equipment interactions, environmental hazards, and operational state in real time across thousands of cameras in manufacturing, logistics, retail, and pharmaceutical environments. Safety was our wedge; it proved our platform works. Now customers are pulling us into operations: equipment utilization, workflow compliance, process efficiency. Every new use case runs through the perception team. We're hiring a Tech Lead Manager to own the applied ML work that drives every new capability we ship. You'll set technical direction, write code, make architecture calls, and build a small team of engineers who take modern ML (VLMs, segmentation, tracking, temporal models) and turn it into things that work in real warehouses, on all kinds of cameras, for demanding customers. This is a hands-on role. You'll ship weekly, debug production problems, sit on customer calls, and own outcomes end to end. If you want a research org behind you, this isn't it. If you want to see your model running in 200 facilities weeks after you trained it, read on. WHAT YOU'LL DO - Set technical direction for Voxel's vision and ML capabilities: what we build, how we build it, how we know it works. - Hire and lead a small team of applied ML engineers. Set the bar, set the goals, set the culture. - Stay in the code. Architecture decisions, model reviews,

Machine Learning: Multimodal Foundation Models San Francisco The Bot Company We're building a helpful robot for every home. We're a small team of engineers, designers, and operators based in San Francisco. Our team comes from Tesla, Cruise, OpenAI, Google, Pixar, and many other great companies. In the past we've shipped to hundreds of millions of users and know what it takes to build amazing products and experiences. Our team is deliberately lean to promote rapid decision making and do away with bureaucracy and hierarchy. Everyone is an IC and is empowered with massive scope, radical ownership, and direct responsibility. We work across the stack with a culture built for rapid iteration and fast execution. What we look for in all candidates All roles at The Bot Company demand extreme sharpness and the ability to move fast in high-intensity environments. Throughout the process, we expect candidates to demonstrate: - Exceptional mental acuity: you think quickly, learn instantly, and reason across unfamiliar domains. - Engineering curiosity: you naturally dig into how systems work, even outside your specialty. - High performance mindset: you move fast, handle ambiguity, and excel when the environment is demanding. Machine Learning: Multimodal Foundation Models We are building unified foundation models that natively reason across text, image, video, and kinematics to drive intelligent robotic policies. You will work on large multi-modal networks and own the entire stack from data to training and deploying models. What You'll Do - Build Native Multimodal Policies: Develop architectures where vision, language, and more

Senior Site Reliability Engineer United Kingdom, London, London, United Kingdom Thought Machine's mission is bold - to properly and permanently rid the world's banks of legacy technology. To achieve this, we have developed the foundations of modern banking through core and payments technology which run natively in the cloud. What we are attempting is hard and means we need great people working together to build great technology. We have grown rapidly in the past few years - growing our team to more than 550 individuals across offices in London, New York, Singapore, Sydney and our newly established Engineering Hub in Lisbon. We have raised more than £500m in funding and our investors include Molten Ventures, Eurazeo, Intesa Sanpaolo, Temasek, Nyca Partners, JPMorgan Chase Strategic Investments, Standard Chartered Ventures, and more. We have created a culture that enables our team to produce the best work in the industry while ensuring we have fun along the way. We're regularly cited as having a fantastic workplace culture and have been recognised by Sifted magazine as having one of the highest Glassdoor ratings for a UK fintech company and the industry's most generous employee share package. Named one of the world's most innovative fintechs by Global Finance Magazine, we were also recognised by the Financial Times as one of Europe's fastest-growing companies for two consecutive years-and a UK Best Employer for 2026. Thought Machine's Site Reliability Engineers are the guardians of mission-critical systems for the world's most influential financial institutions. As a member of

Machine Learning Engineer Belfast - 20 Adelaide Street posted: Posted 30+ Days Ago

Engineering Manager Portugal, Lisbon, Lisbon, Portugal Thought Machine's mission is bold - to properly and permanently rid the world's banks of legacy technology. To achieve this, we have developed the foundations of modern banking through core and payments technology which run natively in the cloud. What we are attempting is hard and means we need great people working together to build great technology. We have grown rapidly in the past few years - growing our team to more than 550 individuals across offices in London, New York, Singapore, Sydney and our newly established Engineering Hub in Lisbon. We have raised more than £500m in funding and our investors include Molten Ventures, Eurazeo, Intesa Sanpaolo, Temasek, Nyca Partners, JPMorgan Chase Strategic Investments, Standard Chartered Ventures, and more. We have created a culture that enables our team to produce the best work in the industry while ensuring we have fun along the way. We're regularly cited as having a fantastic workplace culture and have been recognised by Sifted magazine as having one of the highest Glassdoor ratings for a UK fintech company and the industry's most generous employee share package. Named one of the world's most innovative fintechs by Global Finance Magazine, we were also recognised by the Financial Times as one of Europe's fastest-growing companies for two consecutive years-and a UK Best Employer for 2026. Software Engineering is a key role within Thought Machine. As an engineering-focused company, we take pride in our engineering excellence, adopting best practices, and utilising modern

AI Scientist London, United Kingdom posted: Posted 28 Days Ago

Core Banking developer Dublin, Ireland This role suits candidates with direct Thought Machine experience or a comparable background building digital banking products on modern core platforms, with strong engineering fundamentals and an app...

Senior AI Scientist Durham, North Carolina, United States of America posted: Posted Yesterday

Software Engineer (Infrastructure) United Kingdom, London, London, United Kingdom Thought Machine's mission is bold - to properly and permanently rid the world's banks of legacy technology. To achieve this, we have developed the foundations of modern banking through core and payments technology which run natively in the cloud. What we are attempting is hard and means we need great people working together to build great technology. We have grown rapidly in the past few years - growing our team to more than 550 individuals across offices in London, New York, Singapore, Sydney and our newly established Engineering Hub in Lisbon. We have raised more than £500m in funding and our investors include Molten Ventures, Eurazeo, Intesa Sanpaolo, Temasek, Nyca Partners, JPMorgan Chase Strategic Investments, Standard Chartered Ventures, and more. We have created a culture that enables our team to produce the best work in the industry while ensuring we have fun along the way. We're regularly cited as having a fantastic workplace culture and have been recognised by Sifted magazine as having one of the highest Glassdoor ratings for a UK fintech company and the industry's most generous employee share package. Named one of the world's most innovative fintechs by Global Finance Magazine, we were also recognised by the Financial Times as one of Europe's fastest-growing companies for two consecutive years-and a UK Best Employer for 2026. At Thought Machine, our Software Engineers specialised in Infrastructure play a crucial role in deploying and maintaining our cutting-edge software, developing tools and

AI Platform Engineer, Capabilities San Francisco Bay Area, San Francisco, California, United States About Brain Co. Brain Co. is an applied AI startup co-founded by Jared Kushner and Elad Gil, and backed by leading Silicon Valley builders including Patrick Collison and Andrej Karpathy. We are building AI applications for the world's most important institutions, delivering impact on real-world problems across governments, healthcare systems, and critical industries. Our progress so far: - Automated construction permitting for a sovereign government → 80% faster, unlocking $375M+ in value - Optimized supply chains for a leading global energy company → 30% lower cost, 99% reliability, preventing $100M+ in losses - Streamlined hospital patient care across national health systems → 40% better outcomes, 80% less admin work Company momentum: - Raised a $55M Series A from leading investors - Built a team of 70+ AI experts from Tesla, Google DeepMind, NVIDIA, and Databricks At Brain Co., we focus on applying frontier AI to real institutional challenges, working alongside governments, healthcare systems, and critical industries to modernize how essential services operate. We are looking for leaders who want to help bring new technology into institutions that impact millions of people. About the Role: As a core backend engineer at Brain Co., you will build the shared technical capabilities that help us scale our AI products quickly, safely, and reliably. You will take ambiguous product and technical challenges, turn them into clear system designs, and ship robust platforms that support real-world AI applications for the world's most

Senior Software Engineer (Infrastructure) Portugal, Lisbon, Lisbon, Portugal Thought Machine's mission is bold - to properly and permanently rid the world's banks of legacy technology. To achieve this, we have developed the foundations of modern banking through core and payments technology which run natively in the cloud. What we are attempting is hard and means we need great people working together to build great technology. We have grown rapidly in the past few years - growing our team to more than 550 individuals across offices in London, New York, Singapore, Sydney and our newly established Engineering Hub in Lisbon. We have raised more than £500m in funding and our investors include Molten Ventures, Eurazeo, Intesa Sanpaolo, Temasek, Nyca Partners, JPMorgan Chase Strategic Investments, Standard Chartered Ventures, and more. We have created a culture that enables our team to produce the best work in the industry while ensuring we have fun along the way. We're regularly cited as having a fantastic workplace culture and have been recognised by Sifted magazine as having one of the highest Glassdoor ratings for a UK fintech company and the industry's most generous employee share package. Named one of the world's most innovative fintechs by Global Finance Magazine, we were also recognised by the Financial Times as one of Europe's fastest-growing companies for two consecutive years-and a UK Best Employer for 2026. Software Engineering is a key role within Thought Machine. As an engineering-focused company, we take pride in our engineering excellence, adopting best practices, and

AIML - Sr Machine Learning Engineer, Responsible AI Cupertino, United States of America Would you like to play a part in building the next generation of generative AI applications at Apple? We're looking for Machine Learning Engineers to work on ambitious projects that will impact the future of Apple, our products, and the broader world. This role is directed at assessing, quantifying, and improving the safety and inclusivity of Apple's Generative-AI powered features and products. In this role you'll have the opportunity to tackle innovative problems in machine learning, particularly focused on large language models for text generation, diffusion models for image generation, and mixed model systems for multimodal applications. As a member of Apple's Responsible AI group you will be working on a wide array of new features and research in the generative AI space. Our team is currently interested in large generative models for vision and language, with particular interest on Responsible AI, safety, fairness, robustness, explainability, and uncertainty in models. This role focuses on developing, carrying-out, interpreting, and communicating pre- and post-ship evaluations of the safety of Apple Intelligence features. Both human grading and model-based auto-grading are thoughtfully leveraged to power these evaluations. Additionally, this role researches and develops auto-grading methodology & infrastructure to benefit ongoing and future Apple Intelligence safety evaluations. Producing safety evaluations that uphold Apple's Responsible AI values requires thoughtful data sampling, creation, and curation for evaluation datasets; high quality, detailed annotations and careful auto-grading to assess feature performance; and mindful analysis to understand

Senior/Staff Machine Learning Engineer Redwood City About Dexterity At Dexterity, we believe robots can positively transform the world. Our breakthrough technology frees people to do the creative, inspiring, problem-solving jobs that humans do best by enabling robots to handle repetitive and physically difficult work. We're starting with warehouse automation, where the need for smarter, more resilient supply chains impacts millions of lives and businesses worldwide. Dexterity's full-stack robotics systems pick, move, pack, and collaborate with human-like skill, awareness, and learning capabilities. Our systems are software-driven and hardware-agnostic and have already picked 100+ million goods in production. And did we mention we're customer-obsessed? Every decision, large and small, is driven by one question - how can we empower our customers with robots to do more than they thought was possible? Dexterity is one of the fastest-growing companies in robotics, backed by world-class investors such as Kleiner Perkins, Lightspeed Venture Partners, and Obvious Ventures. We're a diverse and multidisciplinary team with a culture built on passion, trust, and dedication. Come join Dexterity and help make intelligent robots a reality! About the Role As a Senior/Staff Machine Learning Engineer, you will be working on a myriad of challenges related to robot task and action planning. You will leverage techniques from machine learning to solve hard sequential decision problems that require reasoning about the physical world and its dynamics. You will also stay abreast of the latest progress in imitation learning, reinforcement learning, and other related fields in order to further develop Dexterity's technology

AIML - Senior Machine Learning Engineer - Data Science, Responsible AI and Safety Cupertino, United States of America Would you like to play a part in building the next generation of generative AI applications at Apple? We're looking for Machine Learning Engineers to work on ambitious projects that will impact the future of Apple, our products, and the broader world. This role is directed at assessing, quantifying, and improving the safety and inclusivity of Apple's Generative-AI powered features and products. In this role you'll have the opportunity to tackle innovative problems in machine learning, particularly focused on large language models for text generation, diffusion models for image generation, and mixed model systems for multimodal applications. As a member of Apple's Responsible AI group you will be working on a wide array of new features and research in the generative AI space. Our team is currently interested in large generative models for vision and language, with particular interest on Responsible AI, safety, fairness, robustness, explainability, and uncertainty in models. This role focuses on developing, carrying-out, interpreting, and communicating pre- and post-ship evaluations of the safety of Apple Intelligence features. Both human grading and model-based auto-grading are thoughtfully leveraged to power these evaluations. Additionally, this role researches and develops auto-grading methodology & infrastructure to benefit ongoing and future Apple Intelligence safety evaluations. Producing safety evaluations that uphold Apple's Responsible AI values requires thoughtful data sampling, creation, and curation for evaluation datasets; high quality, detailed annotations and careful auto-grading to assess feature performance;

Member of Technical Staff, Tech Lead San Francisco, CA, San Francisco, California, United States, New York, NY TL;DR: Listen teaches AI what people actually think and want. We're Sequoia-backed, raised $100M, and our customers include Anthropic, Google, and Cursor. We're hiring engineers who can build a complex AI-native product on a small team of former founders and top-tier builders. Background As AI gets better at building things, the bottleneck shifts to knowing what to build. We're the bridge between AI systems and what humans actually want. Today our customers are companies. Soon, AIs themselves will be our customers. Our platform runs AI-moderated video interviews at massive scale. We find the right people from a network of millions, our AI conducts open-ended conversations with thousands of them in parallel, and we surface what to build next. What used to take research teams weeks per study, we do in hours. Where it's going: every interview feeds a human preference model. We simulate human behavior at scale: how people react to new ideas, how they make decisions, how preferences shape markets, and how change ripples through society. We expose this as the Human API. An AI agent writes code, asks Listen whether users would actually want a feature, gets a grounded answer back, and iterates. Closed-loop product development at AI speed. Every coding agent will eventually need this signal. Company highlights - Series B with $100M raised from Sequoia, Conviction, Ribbit, AI Grant, and Pear VC. - Selective team of - Customers include

Senior AI Engineer SAN JOSE posted: Posted 2 Days Ago

Client Success Director (Thai Speaking) Singapore Thought Machine's mission is bold - to properly and permanently rid the world's banks of legacy technology. To achieve this, we have developed the foundations of modern banking through core and payments technology which run natively in the cloud. What we are attempting is hard and means we need great people working together to build great technology. We have grown rapidly in the past few years - growing our team to more than 550 individuals across offices in London, New York, Singapore, Sydney and our newly established Engineering Hub in Lisbon. We have raised more than £500m in funding and our investors include Molten Ventures, Eurazeo, Intesa Sanpaolo, Temasek, Nyca Partners, JPMorgan Chase Strategic Investments, Standard Chartered Ventures, and more. We have created a culture that enables our team to produce the best work in the industry while ensuring we have fun along the way. We're regularly cited as having a fantastic workplace culture and have been recognised by Sifted magazine as having one of the highest Glassdoor ratings for a UK fintech company and the industry's most generous employee share package. Named one of the world's most innovative fintechs by Global Finance Magazine, we were also recognised by the Financial Times as one of Europe's fastest-growing companies for two consecutive years-and a UK Best Employer for 2026. The Client Success Director (CSD) is accountable for ensuring Clients successfully adopt and scale our platform to achieve their contracted outcomes. The primary measure of success

Senior Machine Learning Engineer, AI Platform San Jose posted: Posted 30+ Days Ago

Supply Clerk (Vending Machine) NF-02 McAlester, Oklahoma Summary This position is located at McAlester Army Ammunition Plant in McAlester, Oklahoma.. Incentives and Bonuses Incentives will not be paid. Duties Orders and maintains adequate supply levels and stock usage reports for assigned vending and or coin operated video game machines located on the installation. Places orders with local vendors based on stock levels. Responsible for collecting and safeguarding collected revenue from machines. May perform minor repair and maintenance of vending machines. Operates a motor vehicle to deliver goods from stock room to various vending machine locations. Evaluation Your Application Matters: How We Will Review It We want to help you put your best foot forward! Please take time to carefully follow all application instructions - missing information or skipped steps could impact your eligibility. Your application will be thoughtfully reviewed to see how well your experience and qualifications align with the requirements listed in this announcement. This includes your resume, supporting documents, and responses to the assessment questionnaire. We will consider your responses to our application questionnaire. If you're tentatively qualified, we'll take a closer look to ensure your questionnaire responses match the experience reflected in your resume and documentation. Note: If it's later found that qualifications or experience were overstated, it may affect your consideration for the position - so honesty and clarity are key. Understanding Eligibilities: What You Can Claim When Applying When you apply for a federal position through USAJOBS or USA Staffing, you may be eligible for