Are you eager to explore the frontiers of AI? Join us as a founding member of the Flower Frontier Model Team, an innovative group at Flower Labs. Our mission is to develop groundbreaking models that merge state-of-the-art practices with Flower's revolutionary decentralized learning techniques. This role takes a significantly different approach compared to traditional frontier labs, facilitating GPU scaling while unlocking new data silos for frontier model training.Our goal is to create models with superhuman capabilities across various domains, including science, health, finance, drug discovery, and beyond. This is your chance to help innovate and establish the training paradigms that will shape the next decade of artificial intelligence and work on technologies that will influence future developments in the field.Position OverviewPreference will be given to candidates with post-training expertise, but we encourage all passionate individuals with a proven record of excellence to apply, regardless of their prior experience.As a founding Research Engineer, you will be instrumental in developing state-of-the-art LLMs and foundational models within a compact, high-impact team of professionals with diverse research and engineering backgrounds. You will have the opportunity to influence every aspect of the scientific groundwork for our frontier models. Expect to be hands-on, transforming your best ideas into functional systems and working closely with the team to scale the most effective strategies. The techniques you create will contribute to world-leading models that will be open-sourced and integrated into new Flower Lab products.We anticipate that you will infuse creativity into your work while maintaining a methodical approach to experimentation and remain informed about the latest advancements from other AI laboratories. This knowledge will guide how you design and implement techniques and conduct experiments across all stages relevant to frontier model development: data curation, evaluations, pre-training, and post-training. Everything is on the table as we aim to release our first series of models. While experience in these areas is valued, a strong emphasis on problem-solving, on-the-job learning, and collaborative work to effectively leverage the team's diverse talents is essential for success.

Join prior-labs as a Senior Machine Learning Infrastructure Engineer, where you will play a pivotal role in designing and optimizing scalable ML infrastructure. Collaborate with cross-functional teams to enhance the performance and reliability of our machine learning systems. Your expertise will help drive innovation and efficiency within our organization.

Join Prior Labs as a Machine Learning Engineer specializing in Open Source projects. In this pivotal role, you will collaborate with a dynamic team to develop innovative machine learning solutions that leverage open-source technologies. Your contributions will be vital in advancing our mission to make machine learning accessible and impactful.We're looking for passionate individuals who are eager to push the boundaries of technology and drive meaningful change through their work.

Join Our Team at Prior LabsPrior Labs is at the forefront of innovation, developing foundation models that comprehend tabular data—an essential component for both science and business. While foundation models have revolutionized text and images, structured data has largely been overlooked. We aim to seize this $600 billion opportunity to fundamentally transform how organizations interact with scientific, medical, financial, and business data.Our Achievements: We are a leading organization in structured data machine learning. Our groundbreaking TabPFN v2 model was featured in Nature, establishing a new benchmark for tabular machine learning. Since its launch, we have amplified our model capabilities over 20 times, garnered over 2.5 million downloads, and achieved 5,500+ stars on GitHub. Our rapid adoption rate is evident across both research and industry as we develop the next generation of tabular foundation models and commercialize them with leading enterprises in Europe and the US.About Our Team: We are a small yet select group of over 20 engineers and researchers, handpicked from a pool of 5,000 candidates. Our team members hail from esteemed organizations such as Google, Apple, Amazon, Microsoft, G-Research, Jane Street, Goldman Sachs, and CERN. We are led by the creators of TabPFN and are advised by world-renowned AI researchers, including Bernhard Schölkopf and Turing Award winner Yann LeCun. Learn more about our team here.What's Next: Supported by top-tier investors and experts from Hugging Face, DeepMind, and Silo AI, we're experiencing rapid growth. This is your chance to join us and help shape the future of structured data AI. Explore our manifesto.

Join Our Innovative TeamAt Prior Labs, we are pioneering the development of foundation models that adeptly comprehend tabular data, which serves as the cornerstone of both scientific and business endeavors. While foundation models have revolutionized the fields of text and image processing, structured data has largely been overlooked. We are seizing the opportunity to address this $600 billion market and fundamentally transform how organizations manage scientific, medical, financial, and business data.Our Achievements: We stand at the forefront of structured data machine learning. Our TabPFN v2 model, featured in Nature, has set a new benchmark in tabular machine learning. Since its launch, we have enhanced our model capabilities over 20 times, achieved over 2.5 million downloads, garnered more than 5,500 stars on GitHub, and are witnessing rapid adoption across both research and industry sectors. We are currently developing the next generation of tabular foundation models and actively commercializing them in collaboration with global enterprises in Europe and the U.S.About Our Team: We are a compact, highly selective team of over 20 engineers and researchers, chosen from more than 5,000 applicants. Our team includes talents from industry giants like Google, Apple, Amazon, Microsoft, G-Research, Jane Street, Goldman Sachs, and CERN. We are led by the creators of TabPFN and supported by renowned AI researchers, including Bernhard Schölkopf and Turing Award winner Yann LeCun. Meet our exceptional team here.Looking Ahead: With backing from top-tier investors and leaders from Hugging Face, DeepMind, and Silo AI, we are experiencing rapid growth. This is an exciting opportunity to join us and contribute to shaping the future of structured data AI. Read our manifesto.Your ImpactIn this role, you will do more than simply deploy models; you will play a crucial role in delivering transformative solutions that redefine how organizations leverage data. You will work at the intersection of advanced AI technology and practical applications, collaborating closely with our key strategic partners.

Join Our Innovative TeamAt Prior Labs, we are revolutionizing the way organizations interact with structured data, the cornerstone of science and business. While foundation models have significantly advanced the fields of text and image processing, structured data has largely been overlooked. We are seizing a $600 billion opportunity to transform how scientific, medical, financial, and business data are utilized.Leading the Charge: We are recognized as the premier organization in structured data machine learning. Our TabPFN v2 model, highlighted in Nature, has set a new benchmark in tabular machine learning. Our capabilities have expanded over 20 times since launch, with over 2.5 million downloads and 5,500+ stars on GitHub, leading to rapid adoption in both research and industry. We are now advancing the next generation of tabular foundation models and partnering with major enterprises across Europe and the US.Our Team: We are a tight-knit team of over 20 engineers and researchers, handpicked from a pool of more than 5,000 applicants, with backgrounds from renowned companies like Google, Apple, Amazon, Microsoft, G-Research, Jane Street, Goldman Sachs, and CERN. Our team is guided by the creators of TabPFN and supported by leading AI experts such as Bernhard Schölkopf and Turing Award winner Yann LeCun. Get to know our team here.Looking Ahead: With backing from top-tier investors and leaders from Hugging Face, DeepMind, and Silo AI, we are rapidly expanding. This is the perfect moment to join us and help shape the future of structured data AI. Explore our manifesto.

Join Our Innovative TeamAt Prior Labs, we are pioneering the development of foundation models that excel in understanding tabular data, which is essential for the realms of science and business. While foundation models have revolutionized the processing of text and images, structured data remains an untapped frontier. We aim to seize this $600 billion opportunity to transform the way organizations engage with scientific, medical, financial, and business data.Our Momentum: We stand as a global leader in structured data machine learning. Our TabPFN v2 model, featured in Nature, has set new benchmarks in tabular machine learning. Since its launch, we have enhanced model capabilities by over 20 times, recording more than 2.5 million downloads and over 5,500 GitHub stars, along with a rapidly growing adoption rate across research and industry. We are currently advancing the next generation of tabular foundation models and actively commercializing them within leading enterprises across Europe and the US.Meet Our Team: Our diverse team comprises over 20 engineers and researchers, meticulously selected from over 5,000 applicants, with impressive backgrounds from Google, Apple, Amazon, Microsoft, G-Research, Jane Street, Goldman Sachs, and CERN. Led by the creators of TabPFN and mentored by esteemed AI researchers like Bernhard Schölkopf and Turing Award winner Yann LeCun, we are committed to excellence. Discover more about our team here.What Lies Ahead: With the backing of elite investors and leaders from Hugging Face, DeepMind, and Silo AI, we are experiencing rapid growth. This is an exciting moment to join us and play a crucial role in shaping the future of structured data AI. Read our manifesto.Position OverviewWe are seeking exceptional full stack engineers to contribute to the development of the ML Platform that underpins our tabular foundation model offerings. This role presents a unique opportunity to work at the intersection of data science, agents, user experience (UX), and tangible economic impact.Responsibilities:Take ownership of our user-facing frontend and backend applications to develop cutting-edge data science tools.Collaborate with product and research teams to transform new model and agent capabilities into actionable production features.Design and implement high-trust, scalable systems.Focus on optimizing for speed, reliability, and security.Current technology stack includes JavaScript/TypeScript, among others.

Company Overview At Orcrist Technologies, we are pioneering the future of data intelligence with our Orcrist Intelligence Platform (OIP). This secure, Kubernetes-native system is designed for deployment as Software as a Service (SaaS) or can be self-hosted/on-premises, accommodating even air-gapped missions. Our mission is to seamlessly integrate data processing, machine learning, and user-centric design for defense, law enforcement, and corporate teams. Role Overview As a Machine Learning Engineer, you will be instrumental in productionizing NLP, audio, and document models that enhance the insight experiences provided by OIP. You will take full ownership of model packaging, deployment, monitoring, and evaluation, collaborating closely with research and product teams to ensure the delivery of reliable insights globally. Your Responsibilities Package and deploy various models (ASR, translation, OCR, NER, summarization) utilizing Triton/KServe on Kubernetes. Develop evaluation pipelines (WER, BLEU, F1, latency, cost) and automate release gating processes. Manage streaming and batch inference through Kafka, Temporal, and backfill tooling. Monitor model performance and quality using Prometheus, Grafana, and Evidently; optimize inference costs and performance metrics. Collaborate with TypeScript teams to design payload schemas, contracts, and establish human-in-the-loop feedback mechanisms. Qualifications 4 to 8+ years of experience in ML engineering or MLOps, with a proven track record of deploying models to production. Proficiency in Python and frameworks such as PyTorch/Transformers, along with experience using Triton/KServe or similar technologies. Familiarity with Kubernetes, GitOps, CI/CD practices, and GPU workload management. Strong understanding of evaluation metrics, monitoring techniques, and annotation workflows. Eligibility to work in Germany; export-control screening may be required for certain projects. Preferred Qualifications Experience with Temporal, Beam/Flink, or Ray Serve; familiarity with ONNX/TensorRT optimization. Proficiency in the German language (B1+) and experience with defense or public safety datasets. Knowledge of WhisperX, DeepStream/GStreamer, or vector search integrations. What We Offer A modern MLOps stack including Triton, Temporal, Kafka, MLflow, Weights & Biases, Evidently, and Kubernetes. A remote-first work environment in Germany, with regular meetups in Berlin, 30 days of vacation, and a budget for equipment and learning.

Machine Learning Engineer Company Overview At Orcrist Technologies, we are pioneers in building the Orcrist Intelligence Platform (OIP), a cutting-edge Kubernetes-based data intelligence system. Our platform is offered as either SaaS or a self-hosted/on-premises solution, including air-gapped deployments. We integrate data processing, machine learning, and artificial intelligence within a modern web application to empower mission-critical clients across both public and private sectors. Role Overview As a Machine Learning Engineer, you will spearhead the incubation and validation of new ML initiatives from conception to execution. In this innovative role, you will create adoption-ready prototype vertical slices that encompass data flows, model serving, evaluation, and seamless product integration. You will ensure clear handoff of artifacts to delivery teams so they can effectively productize and maintain them for the long haul. Key Responsibilities Develop ML prototype vertical slices that bridge data ingestion and processing with inference and end-user product outcomes (such as search functionalities, insights generation, and user experience flows). Establish evaluation harnesses and decision-making artifacts including datasets, baselines, and performance metrics (quality, latency, cost), along with actionable go/no-go recommendations. Package prototypes for seamless adoption: containerize services, specify reproducible deployment strategies, and create comprehensive runbooks/checklists. Collaborate with Research and Data Engineering teams for dataset curation, annotation processes, experiment tracking, and iterative improvements. Ensure operational credibility of prototypes through instrumentation, monitoring, and foundational security/compliance practices (including handling of personally identifiable information and provenance considerations). Candidate Profile A minimum of 3 years of experience in ML engineering or MLOps, with a proven track record of delivering tangible systems. Proficient in Python and experienced with PyTorch/Transformers; adept at transforming models from notebooks into deployable services. Hands-on experience with Kubernetes and containerization; capable of deploying and troubleshooting within production-like environments, including offline or air-gapped constraints. A strong evaluation mindset and monitoring discipline; effective in clearly articulating trade-offs. Eligibility to work in Germany; EU or NATO citizenship is preferred, and export-control screening applies. Preferred Qualifications Experience with GPU serving and optimization techniques (e.g., Triton/KServe, ONNX/TensorRT, batching, quantization). Familiarity with streaming and pipeline tools (e.g., Kafka, Ray, Beam/Flink/Spark) and integrations involving search, vector, and graph technologies. Proficiency in the German language (B1+) and/or experience working with regulated or public-sector datasets and workflows. What We Offer A modern ML stack designed to operate within real-world constraints: Kubernetes, streaming technologies, and hybrid/on-prem/air-gapped deployments. A remote-first work environment in Germany, complemented by regular workshops in Berlin, 30 days of vacation, and support for equipment and learning budgets. High impact: your prototypes will pave the path for groundbreaking solutions.

Cresta is revolutionizing the way customer conversations are transformed into a competitive edge by harnessing the full potential of the contact center. Our innovative platform merges cutting-edge AI with human intelligence, allowing contact centers to uncover valuable customer insights, streamline conversations, and empower team members to work more efficiently. With roots in the elite Stanford AI lab, Cresta's co-founder and chairman is Sebastian Thrun, the visionary behind Google X, Waymo, and Udacity. Our leadership team also includes CEO Ping Wu, co-founder of Google Contact Center AI, and co-founder Tim Shi, an early member of OpenAI. Embark on an exciting journey with us as we redefine the future of work through AI. The future of work is now, and it starts at Cresta.About the Role:At Cresta, we are committed to crafting advanced Machine Learning systems designed to facilitate real-time, intelligent interactions with customers. Our team develops models and platforms capable of processing vast amounts of multimodal data—particularly focusing on speech and text—to derive insights, enhance quality, and provide actionable intelligence at scale. This role emphasizes advancing model evaluation, measurement, and quality improvements, particularly in Automatic Speech Recognition (ASR) and subsequent NLP systems. You will be responsible for designing comprehensive evaluation frameworks, defining quality metrics, and driving systematic enhancements to model accuracy, robustness, and reliability.

Role overview Toloka AI seeks a Freelance Machine Learning Engineer to contribute to remote projects connected to Stuttgart, Baden-Württemberg, Germany. The position centers on building and enhancing machine learning models used in advanced AI applications. What you will do Develop and improve machine learning models for various AI projects Apply technical knowledge to help design and implement new AI applications Location This contract position is fully remote. Candidates should be based in or near Stuttgart, Baden-Württemberg, Germany.

Join Almedia, a dynamic and innovative company where ambition meets opportunity. As we strive to become Germany’s next bootstrapped unicorn, we are proud to be recognized as Europe’s third fastest-growing company in 2025 according to the FT1000.At Almedia, we are revolutionizing the marketing landscape by enabling our vast community of over 60 million users to earn rewards for interacting with our advertisers' products, providing a unique approach to user acquisition for major global brands.Machine Learning EngineerIn this pivotal role, you will be responsible for the design, development, and scaling of production-grade machine learning solutions that drive the innovation of Almedia’s offerings and support our growth trajectory.This is a hands-on position where you will actively engage in coding, development, and deployment of solutions.Key Challenges You Will Tackle:Creating and optimizing user reward systems tailored to player behavior and market trends.Spearheading the development of personalized, real-time reward mechanisms.Identifying and addressing underperforming reward initiatives and their underlying issues.Your Responsibilities Include:Overseeing the complete delivery lifecycle: develop, deploy, and optimize scalable solutions and services.Providing technical guidance on ML projects, upholding best practices and ensuring high coding standards.Aligning technical capabilities with business goals to capitalize on high-value opportunities.Utilizing advanced statistical and causal inference techniques to secure robustness and reliability in solutions.Collaborating with product and engineering teams to convert business challenges into predictive, data-driven solutions.Qualifications Required:Demonstrated expertise in building, deploying, and maintaining production-level solutions and services, preferably in adtech or high-scale environments.Solid understanding of statistical analysis (A/B testing, regression, probability).Proficient in programming with Python and SQL, with practical experience in cloud technologies.Proven ability to mentor and guide ML engineers and cross-functional colleagues.Excellent communication skills and a collaborative mindset.

Join Our Team as a Senior Machine Learning EngineerFull-time | Munich | Seed Stage | Equity + SalaryAt Knowlix, our mission is to revolutionize small business productivity by harnessing the power of AI. We aim to establish ourselves as the leading platform for human-AI and AI-to-AI collaboration.As a member of our early-stage team, you will have the unique opportunity to influence our product development and help shape a platform that could serve millions.We prioritize speed and quality, embracing a culture of rapid iteration and continuous improvement. If you are passionate about leveraging AI to innovate and scale solutions, we want you on our team.Why Choose Knowlix?Backed by prominent investors, we are a well-funded startup with ambitious goals.Our technology is already making waves with early adopters experiencing its benefits.We are tackling a vast market with a product designed to redefine workplace collaboration.As one of the first hires, your contributions will have a significant impact on our success.We believe that focused iteration is key to rapid development.This is not just a job; it's your chance to help create a lasting legacy.Your RoleYou will be responsible for designing and deploying cutting-edge machine learning systems, specifically focusing on LLM-driven agents and self-optimizing workflows. This hands-on position will require you to develop robust data pipelines, foster rapid experimentation, and ensure continuous model enhancement in a dynamic startup environment.Your ResponsibilitiesCreate LLM-based agents, implement tool-using workflows, and design autonomous self-improvement systems.Design, train, and assess machine learning models in the areas of NLP/LLM, computer vision, and data retrieval.Build data pipelines, develop training code, and create tools for experimentation and automated deployment.Utilize PyTorch for model development and tools like Weights & Biases for experiment tracking.Implement performance monitoring, including oversight for drift and safety measures.

Join 10xteam as a Machine Learning Engineer & AI Trainer in a freelance capacity. This role offers the flexibility to work remotely, dedicating 8-20 hours per week to help us innovate and excel in AI-driven projects. As an integral part of our team, you will be responsible for training and optimizing machine learning models, contributing to various applications of artificial intelligence.

Take the lead in shaping the future of conversation.Join Rasa and innovate!At Rasa, we believe that conversation is the essence of connection. It allows us to foster relationships with empathy and understanding, bridging differences and uniting diverse backgrounds.Rasa symbolizes unity and clarity. We challenge norms and seek answers through relentless innovation and a clear vision, revolutionizing how individuals engage with organizations through cutting-edge AI technology.We invite you to bring your unique perspective to our mission.ROLE OVERVIEWWe are in search of an Engineering Manager to guide our Voice team at Rasa, directly reporting to the Director of Engineering. In collaboration with a product manager, you will spearhead the development of advanced features that enhance our Voice capabilities by addressing fundamental machine learning challenges. Your goal: to cultivate a high-performing, empowered engineering team that excels in a dynamic, remote-first environment.KEY RESPONSIBILITIESDesign and optimize team structure, processes, and workflows to ensure efficiency and quality.Guide and mentor engineers in their technical and professional growth.Facilitate collaboration across engineering, product, and design teams.Accountable for your team's delivery, providing ongoing feedback and support.Promote effective asynchronous communication, enabling your team to work independently in a remote setting.Actively engage in enhancing diversity, equity, and inclusion (DEI) throughout hiring and team dynamics.Assist your team by eliminating obstacles, reviewing pull requests, and occasionally contributing to code or prototypes.Our technology stack includes Python, Sanic, asynchronous programming, and event-driven systems, with protocols and patterns involving websockets, SIP, RTP, streaming, and audio processing. The machine learning aspects involve ML as a service, ML evaluation, and prompt engineering.TEAM DYNAMICSOur team currently comprises a Product Manager, a Tech Lead, two backend engineers, and one QA engineer. We operate in sprints, prioritizing proactive communication, iterative and data-driven product development, prototyping, and proofs of concept. We frequently tackle open-ended challenges where research and exploration are paramount.

About UsAt Prior Labs, we are pioneering the development of foundation models designed to comprehend tabular data, which serves as the core of both scientific and business operations. While foundation models have revolutionized text and image processing, structured data has remained largely neglected. We are seizing the opportunity in this $600 billion sector to fundamentally reshape how organizations interact with scientific, medical, financial, and business data.Our Progress: As a global leader in structured data machine learning, our TabPFN v2 model has been featured in Nature, establishing a new benchmark for tabular machine learning. Following its launch, we have enhanced our model's capabilities by over 20 times, achieving more than 2.5 million downloads and over 5,500 GitHub stars, with rapid adoption across both research and industry. We are currently advancing the next generation of tabular foundation models and actively partnering with enterprises globally across Europe and the US.Our Team: Our team comprises over 20 highly skilled engineers and researchers, meticulously selected from a pool of over 5,000 applicants. With backgrounds from top-tier organizations such as Google, Apple, Amazon, Microsoft, G-Research, Jane Street, Goldman Sachs, and CERN, we are led by the creators of TabPFN and receive guidance from esteemed AI researchers, including Bernhard Schölkopf and Turing Award recipient Yann LeCun. Discover more about our team here.What’s Ahead: Supported by premier investors and leaders from Hugging Face, DeepMind, and Silo AI, we are expanding rapidly. Now is the perfect time to join us and help shape the future of structured data AI. Explore our manifesto.Role OverviewAs a member of our data science team, you will work with a revolutionary class of AI models. In the position of Data Scientist at Prior Labs, you will act as a vital bridge between our cutting-edge technology and its practical applications. You will be a super-user of our foundation models, gaining a profound understanding of their capabilities, presenting compelling use cases, and influencing our product roadmap.This multifaceted role will require you to take on various responsibilities and connect different facets of our organization. Here’s how you will make an impact:Power User & Innovator: Engage deeply with our innovative TFMs (such as TabPFN), experiment extensively with unique features like ICL, and discover new applications.

About UsHelsing is a cutting-edge AI company dedicated to advancing defense technologies. Our mission is to safeguard democratic values and ensure that societies can make autonomous decisions while upholding ethical standards. We are committed to responsible technology development and deployment, particularly in the realm of AI.Our team comprises driven engineers, AI experts, and client-facing program managers united by a common purpose: tackling the most challenging and significant problems. We foster a culture of transparency and encourage open discussions surrounding the ethical implications of technology in defense.The PositionAs an AI Research Engineer at Helsing, you will be at the forefront of innovating autonomous decision-making systems for defense. Your work will encompass a wide range of AI applications, including extensive data processing, reinforcement learning agent training, and the development of large-scale foundational models. Collaborating within a diverse team, your responsibilities will include architecting and implementing robust tools and platforms that drive these advancements. You will focus on abstracting complex distributed systems to enhance training efficiency and developer productivity. We seek engineers who can effectively blend machine learning with systems engineering to create scalable solutions.Key Responsibilities:Enhance our integrated deep learning frameworks, built on PyTorch, to make them efficient and user-friendly across various applications.Expand our infrastructure and tooling to facilitate faster and larger-scale distributed training.Devise data strategies to manage extensive datasets effectively.

Join Perplexity as a skilled Machine Learning Research Engineer, where you will play a pivotal role in developing cutting-edge search technologies focusing on retrieval and ranking mechanisms.Key Responsibilities:Proactively enhance search quality through innovative models, data strategies, tools, and other effective means.Design and construct essential components of our advanced search platform and model architecture.Create, train, and fine-tune large-scale deep learning models utilizing frameworks like PyTorch, with an emphasis on distributed training and hardware acceleration for retrieval and ranking.Engage in advanced research on representation learning, including contrastive learning and multilingual, multimodal modeling tailored for search and retrieval applications.Implement and deploy models effectively, ranging from boosting algorithms to large language models, ensuring scalability and performance.Develop and optimize Retrieval-Augmented Generation (RAG) pipelines for accurate grounding and answer generation.Collaborate across Data, AI, Infrastructure, and Product teams to ensure swift and high-quality project delivery.

Join AppLike as a Senior Machine Learning Engineer, where you'll play a pivotal role in developing cutting-edge algorithms and models that elevate our mobile gaming experience. Collaborate with cross-functional teams to innovate and implement machine learning solutions that enhance user engagement and optimize performance metrics.