We are seeking a Research Engineer/Research Scientist to join our Audio team. As a member of this team, you will work across the full stack of audio ML, developing audio codecs and representations, sourcing and synthesizing high-quality audio data, training large-scale speech language models and large audio diffusion models, and developing novel architectures for incorporating continuous signals into LLMs.
\nOur team focuses primarily but not exclusively on speech, building advanced steerable systems spanning end-to-end conversational systems, speech and audio understanding models, and speech synthesis capabilities. The team works closely with many collaborators across pretraining, finetuning, reinforcement learning, production inference, and product to get advanced audio technologies from early research to high-impact real-world deployments.
\nResponsibilities:
\nStrong candidates may also have experience with:
\nRepresentative projects:
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\nWhile experience in one or more of the following areas is a strong plus: large-scale model training, research in 3D computer vision.
\nYou will collaborate closely with researchers, engineers, and product teams to bring advanced 3D modeling and machine learning techniques into real-world applications, ensuring that our technology remains at the forefront of visual innovation. This role involves significant hands-on research and engineering work, driving projects from conceptualization through to production deployment.
\nKey responsibilities include designing, implementing, and training large-scale diffusion models for generating 3D worlds, developing and experimenting with large-scale diffusion models to add novel control signals, adapting to target aesthetic preferences, or distilling for efficient inference, collaborating closely with research and product teams to understand and translate product requirements into effective technical roadmaps, contributing hands-on to all stages of model development including data curation, experimentation, evaluation, and deployment, continuously exploring and integrating cutting-edge research in diffusion and generative AI more broadly, acting as a key technical resource within the team, mentoring colleagues, and driving best practices in generative modeling and ML engineering.
\nIdeal candidate profile includes 3+ years of experience in generative modeling or applied ML roles, extensive experience with machine learning frameworks such as PyTorch or TensorFlow, especially in the context of diffusion models and other generative models, deep expertise in at least one area of generative modeling, strong history of publications or open-source contributions involving large-scale diffusion models, strong coding proficiency in Python and experience with GPU-accelerated computing, ability to engage effectively with researchers and cross-functional teams, clearly translating complex technical ideas into actionable tasks and outcomes, comfortable operating within a dynamic startup environment with high levels of ambiguity, ownership, and innovation.
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\nAt Mistral AI, we believe in the power of AI to simplify tasks, save time, and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life.
\nWe are a global company with teams distributed between France, USA, UK, Germany, and Singapore. We offer a comprehensive AI platform that meets enterprise needs, whether on-premises or in cloud environments. Our offerings include le Chat, the AI assistant for life and work.
\nRole Summary
\nMistral AI is seeking Applied Scientists Interns and Research Engineers Interns to drive innovative research and collaborate with clients on complex research projects. You will develop SOTA models across different modalities such as text, image, and speech. By developing novel methods and research ideas, you will apply these models across a diverse set of use cases and domains.
\nResponsibilities
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\nAbout You
\n• You are fluent in English, and have excellent communication skills. You are at ease explaining complex technical concepts to both technical and non-technical audiences.\n• You're an expert with PyTorch or JAX.\n• You're not afraid of contributing to a big codebase and can find yourself around independently with little guidance.\n• You write clean, readable, high-performance, fault-tolerant Python code.\n• You don't need roadmaps: you just do. You don't need a manager: you just ship.\n• Low-ego, collaborative, and eager to learn.\n• You have a track record of success through personal projects, professional projects, or in academia.
\nBenefits
\n• Competitive salary\n• Food: Daily lunch vouchers\n• Sport: Monthly contribution to a Gympass subscription\n• Transportation: Monthly contribution to a mobility pass
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\nYou should have a deep understanding of generative AI, hands-on experience serving generative deep learning models in production settings, and a track record of working directly with customers, iterating on solutions, and providing tailored support. Proficiency in Python and intuitive understanding of API integrations are also essential. Excellent communication skills, honed through collaborating with non-technical stakeholders, are necessary to adapt your message depending on who's in the room.
\nPrior experience finetuning diffusion models, working with customization tools like ComfyUI, and contributing to open-source projects in the diffusion model space are highly valued. Deploying models on cloud platforms using state-of-the-art serving infrastructure is also desirable.
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\nMember of Technical Staff - Image / Video Generation
\nJob Description
\nWe're the team behind Latent Diffusion, Stable Diffusion, and FLUX,foundational technologies that changed how the world creates images and video. We're creating the generative models that power how people make images and video,tools used by millions of creators, developers, and businesses worldwide. Our FLUX models are among the most advanced in the world, and we’re just getting started.
\nWhy This Role
\nYou'll train large-scale diffusion models for image and video generation, exploring new approaches while maintaining the rigor that helps us distinguish meaningful progress from incremental tweaks. This isn't about following established recipes,it's about running the experiments that clarify which architectural choices matter and which are less impactful.
\nWhat You’ll Work On
\nWhat We’re Looking For
\nRequired Skills
\nPreferred Skills
\nHow We Work Together
\nWe’re a distributed team with real offices that people actually use. Depending on your role, you’ll either join us in Freiburg or SF at least 2 days a week (or one full week every other week), or work remotely with a monthly in-person week to stay connected. We’ll cover reasonable travel costs to make this possible. We think in-person time matters, and we’ve structured things to make it accessible to all. We’ll discuss what this will look like for the role during our interview process.
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\nYou'll need to have deep technical fluency, either in image/video generation or a technical background such as engineering or solutions architecture. You'll also need to have a proven track record in business development and partnerships in AI, cloud, or technical infrastructure. Strong analytical rigor and market research capabilities are essential, as well as the ability to hold technical conversations with engineers and translate them into commercial strategy.
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\nYour primary focus will be on improving our video presence, creating world-class developer documentation, writing tutorials, and engaging directly with the developer community. You will work closely with our research team to shape how developers discover and learn about FLUX.
\nIn this role, you will have the opportunity to build our local presence in the SF developer community and grow our reach online. You will be responsible for running hackathons, creating video tutorials, and maintaining open-source demo repositories.
\nWe are looking for someone with 3+ years of experience in developer relations or a technical role with a public-facing component. You should have a proven track record of technical content creation, up-to-date engineering skills, and working knowledge of AI/ML development.
\nNice to have: experience with Generative Media, finetuning/LORA of FLUX/Diffusion models.
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\nAt Google DeepMind, we've built a unique culture and work environment where long-term ambitious research can flourish. Our special interdisciplinary team combines the best techniques from deep learning, reinforcement learning, and systems neuroscience to build general-purpose learning algorithms.
\nResearch Scientists lead our efforts in developing novel tools, infrastructure, and algorithms towards the end goal of solving and building Artificial General Intelligence.
\nunparalleled opportunities to work with a talented team of researchers and engineers.
\nDrawing on expertise from a variety of disciplines including deep learning, computer vision, language modeling, and advanced generative architectures, our Research Scientists are at the forefront of groundbreaking research.
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\nAt Google DeepMind, we've built a unique culture and work environment where long-term ambitious research can flourish. Our special interdisciplinary team combines the best techniques from deep learning, reinforcement learning, and systems neuroscience to build general-purpose learning algorithms.
\nResearch Scientists lead our efforts in developing novel tools, infrastructure, and algorithms towards the end goal of solving and building Artificial General Intelligence.
\nHaving pioneered research in the world's leading academic and industrial labs, PhDs, post-docs, or professorships, Research Scientists join Google DeepMind to work collaboratively within and across Research fields. They are expected to work with teams on large scale AI, and develop solutions to fundamental questions in machine learning and AI.
\nDrawing on expertise from a variety of disciplines including deep learning, computer vision, language modeling, and advanced generative architectures, our Research Scientists are at the forefront of groundbreaking research.
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\nPreferred Qualifications
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\nArtificial Intelligence could be one of humanity's most useful inventions. At Google DeepMind, we're a team of scientists, engineers, machine learning experts and more, working together to advance the state of the art in artificial intelligence.
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\nThis is an opportunity to join the Gemini App team for devices, bringing Gemini to experiences on XR glasses, smartwatches, cars, headphones, and more! You'll define and lead the product vision for how users interact with AI across a diverse and rapidly expanding ecosystem of hardware, strategically integrating cutting-edge AI capabilities directly into users' daily lives.
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\nThe role of the Research Engineer will be to develop state-of-the-art methods for multimodal generative AI models, with a primary focus on image generation and editing. This role is for the team behind “Nano Banana”.
\nAs a Research Engineer at Google DeepMind, you will lead our efforts in developing novel tools, infrastructure, and algorithms towards the end goal of solving and building Artificial General Intelligence. You will work collaboratively within and across Research fields, drawing on expertise from a variety of disciplines including deep learning, computer vision, language modeling, and advanced generative architectures.
\nKey responsibilities include designing, implementing, and evaluating cutting-edge deep learning algorithms, data curation, and evaluation infrastructure for multimodal generative AI, with a particular emphasis on image synthesis. You will report and present research findings and developments clearly and efficiently both internally and externally, verbally and in writing. You will also suggest and engage in team collaborations to meet ambitious research goals, while also driving significant individual contributions.
\nTo succeed as a Research Engineer at Google DeepMind, we look for the following skills and experience:
\nIn addition, the following would be an advantage:
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\nMistral AI is a pioneering company shaping the future of AI. We believe in the power of AI to simplify tasks, save time, and enhance learning and creativity.
\nRole Summary
\nMistral AI is seeking Applied Scientists Interns and Research Engineers Interns to drive innovative research and collaborate with clients on complex research projects. You will develop SOTA models across different modalities such as text, image, and speech. By developing novel methods and research ideas you will apply these models across a diverse set of use cases and domains.
\nResponsibilities
\nAbout You
\nIt Would Be Great If
\nBenefits
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\nWe work on the bleeding edge and leverage the most powerful pretrained models and algorithms, making it critical that we ensure our AI systems behave safely and align with organisational values.
\nYou will be responsible for designing novel safety evaluation frameworks, curating high-quality data for robust evaluations and training, prototyping new safety capabilities, and developing safety-focused fine-tuning algorithms.
\nWe're looking for outstanding individuals with deep expertise in multimodal AI safety who can translate research insights into practical solutions while being a strong communicator and collaborative teammate.
\nThe ideal candidate takes the initiative in exploring new safety methodologies and enjoys building world-class, trustworthy AI experiences in a fast-paced applied research environment.
\nMicrosoft's mission is to empower every person and every organisation on the planet to achieve more.
\nAs employees we come together with a growth mindset, innovate to empower others, and collaborate to realise our shared goals.
\nEach day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
\nResponsibilities:
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\nCreate and implement comprehensive evaluation frameworks and red-teaming methodologies to assess model safety across diverse scenarios, edge cases, and potential failure modes.
\nBuild automated safety testing systems, generalise safety solutions into repeatable frameworks, and write efficient code for safety pipelines and intervention systems.
\nMaintain a user-oriented perspective by understanding safety needs from user perspectives, validating safety approaches through user research, and serving as a trusted advisor on multimodal safety matters.
\nTrack advances in multimodal safety research, identify relevant state-of-the-art techniques, and adapt safety algorithms to drive innovation in production systems serving millions of users.
\nEmbody our culture and values.
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\nAnthropic'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.
\nYou may be a good fit if you:
\nStrong candidates may also have experience with:
\nRepresentative projects:
\nLogistics
\nEducation requirements: We require at least a Bachelor's degree in a related field or equivalent experience. 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.
\nVisa 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.
\nWe 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.
\nYour 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.
\nHow we're different
\nWe 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 systems that benefit society.
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\nAbout the role
\nAs a Research Engineer you will join a team of 40+ Researchers and Engineers within the R&D Department working on cutting edge challenges in the Generative AI space, with a focus on creating highly realistic, emotional and life-like Synthetic humans through text-to-video. Within the team you’ll have the opportunity to work on the applied side of our research efforts and directly impact our solutions that are used worldwide by over 55,000 businesses. If you are an expert in post-training Diffusion models for generative AI, this is your chance. This is an opportunity to work for a company that is impacting businesses at a rapid pace across the globe.
\nResponsibilities
\nWhat we're looking for:
\nWhy join us?
\nWe’re living the golden age of AI. The next decade will yield the next iconic companies, and we dare to say we have what it takes to become one. Here’s why,
\nOur culture
\nAt Synthesia we’re passionate about building, not talking, planning or politicising. We strive to hire the smartest, kindest and most unrelenting people and let them do their best work without distractions. Our work principles serve as our charter for how we make decisions, give feedback and structure our work to empower everyone to go as fast as possible. You can find out more about these principles here.
\nServing 50,000+ customers (and 50% of the Fortune 500)
\nWe’re trusted by leading brands such as Heineken, Zoom, Xerox, McDonald’s and more. Read stories from happy customers and what 1,200+ people say on G2.
\nProprietary AI technology
\nSince 2017, we’ve been pioneering advancements in Generative AI. Our AI technology is built in-house, by a team of world-class AI researchers and engineers. Learn more about our AI Research Lab and the team behind.
\nAI Safety, Ethics and Security
\nAI safety, ethics, and security are fundamental to our mission. While the full scope of Artificial Intelligence's impact on our society is still unfolding, our position is clear: People first. Always. Learn more about our commitments to AI Ethics, Safety & Security.
\nThe good stuff...
\nYou can see more about Who we are and How we work here: https://www.synthesia.io/careers
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\nResearcher, Pretraining Safety
\nLocation
\nSan Francisco
\nEmployment Type
\nFull time
\nDepartment
\nSafety Systems
\nCompensation
\nThe base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.
\nMore details about our benefits are available to candidates during the hiring process.
\nThis role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions.
\nAbout the Team
\nThe Safety Systems team is responsible for various safety work to ensure our best models can be safely deployed to the real world to benefit the society and is at the forefront of OpenAI's mission to build and deploy safe AGI, driving our commitment to AI safety and fostering a culture of trust and transparency.
\nThe Pretraining Safety team’s goal is to build safer, more capable base models and enable earlier, more reliable safety evaluation during training. We aim to:
\nIn addition, we will conduct the foundational research necessary for understanding how behaviors emerge, generalize, and can be reliably measured throughout training.
\nAbout the Role
\nThe Pretraining Safety team is pioneering how safety is built into models before they reach post-training and deployment. In this role, you will work throughout the full stack of model development with a focus on pre-training:
\nWe collaborate across OpenAI’s safety ecosystem—from Safety Systems to Training—to ensure that safety foundations are robust, scalable, and grounded in real-world risks.
\nIn this role, you will:
\nYou might thrive in this role if you:
\nAbout OpenAI
\nOpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.
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\nAbout the role
\nAs a Research Engineer, you will join a team of 40+ Researchers and Engineers within the R&D Department working on cutting edge challenges in the Generative AI space, with a focus on avatar-centric interactive video diffusion models. Within the team you’ll have the opportunity to work on the applied side of our research efforts and directly impact our solutions that are used worldwide by over 60,000 businesses.
\nResponsibilities
\nWhat we're looking for:
\nWhat will make you stand out:
\nWhy join us?
\nWe’re living the golden age of AI. The next decade will yield the next iconic companies, and we dare to say we have what it takes to become one. Here’s why,
\nOur culture
\nAt Synthesia we’re passionate about building, not talking, planning or politicising. We strive to hire the smartest, kindest and most unrelenting people and let them do their best work without distractions. Our work principles serve as our charter for how we make decisions, give feedback and structure our work to empower everyone to go as fast as possible. You can find out more about these principles here.
\nServing 50,000+ customers (and 50% of the Fortune 500)
\nWe’re trusted by leading brands such as Heineken, Zoom, Xerox, McDonald’s and more. Read stories from happy customers and what 1,200+ people say on G2.
\nProprietary AI technology
\nSince 2017, we’ve been pioneering advancements in Generative AI. Our AI technology is built in-house, by a team of world-class AI researchers and engineers. Learn more about our AI Research Lab and the team behind.
\nAI Safety, Ethics and Security
\nAI safety, ethics, and security are fundamental to our mission. While the full scope of Artificial Intelligence's impact on our society is still unfolding, our position is clear: People first. Always. Learn more about our commitments to AI Ethics, Safety & Security.
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\nYou can see more about Who we are and How we work here: https://www.synthesia.io/careers
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\nAbout the Role
\nAs a Member of Technical Staff, Multimodal Safety, you will work to develop and implement cutting-edge safety methodologies for post-training multimodal large language models to be served to millions of users through Copilot every day. We work on the bleeding edge and leverage the most powerful pretrained models and algorithms, making it critical that we ensure our AI systems behave safely and align with organizational values.
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\nBenefits
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\nWhat you'll do
\nThis Senior Data Scientist role will focus on designing and developing advanced AI-driven solutions for game developers and gamers. The ideal candidate will have strong expertise in Reinforcement Learning (RL), Generative AI agents, and Retrieval-Augmented Generation (RAG) to create intelligent gaming tools and experiences.
\nWhat you need
\nXML job scraping automation by YubHub
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\nWhat you'll do
\nThis role involves working closely with AI engineers, game developers, and software engineers to build cutting-edge AI capabilities that enhance game mechanics, player engagement, and content generation.
\nWhat you need
\nXML job scraping automation by YubHub
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