Machine Learning Software Engineer at Applied Intuition | Stuttgart

About Applied IntuitionApplied Intuition, Inc. is at the forefront of advancing physical AI. Established in 2017 and currently valued at $15 billion, this Silicon Valley-based company is dedicated to developing the digital framework necessary to infuse intelligence into every machine in motion across the globe. Serving critical sectors such as automotive, de…

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.

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.

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.

Role Overview bluefishai is searching for a Senior Staff Applied AI Engineer based in Berlin or working remotely within Germany. This senior technical leader will shape how artificial intelligence is adopted and scaled across the company. The position focuses on driving AI projects that improve developer productivity, streamline workflows, and grow product capabilities. What You Will Do Lead AI-driven initiatives from concept to implementation, targeting real business outcomes. Work directly with the VP of Engineering and partner with engineering, product, and leadership teams to identify and prioritize impactful AI use cases. Establish structure, standards, and clear processes to help teams use AI effectively and sustainably. Integrate AI solutions into software development workflows to help teams deliver faster and more efficiently. Evaluate new and emerging technologies, including advanced AI capabilities, and advise on their practical application for both products and internal operations. Mentor engineers across teams, define best practices, and support the adoption of AI to drive measurable improvements. What Makes This Role Unique bluefishai is at the early stage of its AI journey, with multiple teams exploring different approaches. This role offers the chance to bring clarity, consistency, and vision, helping set the foundation for scalable AI use across the company. Success depends on strong collaboration, influencing stakeholders, and aligning teams around solutions that deliver real results.

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.

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 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 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.

Join Our Internship Program in Berlin!We are excited to announce a full-time, in-person internship opportunity in our Berlin office, lasting between 12 to 24 weeks.Your ResponsibilitiesDrive the advancement of search quality utilizing various models, data, tools, and innovative techniques.Train and fine-tune large-scale deep learning models using PyTorch, employing distributed training methods (e.g., PyTorch Distributed, DeepSpeed, FSDP) and hardware acceleration, with a focus on retrieval and ranking models.Engage in research on representation learning, exploring contrastive learning, multilingual capabilities, evaluation methodologies, and multimodal modeling for enhanced search and retrieval.Design and refine RAG pipelines for effective grounding and answer generation.QualificationsSolid understanding of search and retrieval systems, including quality evaluation metrics and principles.Demonstrated proficiency with PyTorch, particularly in distributed training and performance optimization for large models.A keen interest in representation learning, covering areas such as contrastive learning, dense and sparse vector representations, representation fusion, cross-lingual representation alignment, training data optimization, and robust evaluation methods.A publication record in AI/ML conferences or workshops (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, SIGIR) is a plus.

Join Intercom, the leading AI Customer Service company, dedicated to empowering businesses to deliver exceptional customer experiences.Our AI agent, Fin, stands out as the most sophisticated customer service AI solution available, enabling companies to provide constant, flawless service and revolutionize their customer interactions. Fin seamlessly integrates with our Helpdesk to form the Intercom Customer Service Suite, which offers AI-enhanced support for intricate or high-touch inquiries that necessitate human intervention.Founded in 2011, Intercom is trusted by nearly 30,000 global businesses and is committed to redefining customer service standards. Our core values inspire us to innovate relentlessly, operate with speed and intensity, and consistently provide remarkable value to our clients.We believe Berlin is an ideal city for those who share our passion for speed and innovation. The city boasts a unique combination of deep technical expertise and a vibrant creative culture, making it a hub for top-tier talent eager to collaborate on ambitious projects. With close ties to our R&D centers in Dublin and London, Berlin is where the best minds come together to thrive.As we aim to expand our team by hiring 100 professionals across engineering, AI, data science, product, and design over the next year, this is an exciting opportunity to be among the pioneering R&D talents in the region and leave a lasting mark as we develop the world's leading customer agent.What’s the Opportunity?The Machine Learning team at Intercom is at the forefront of defining new ML features, researching cutting-edge algorithms and technologies, and swiftly delivering prototypes to our customers.We are a highly product-focused team, collaborating closely with Product and Design teams. Our dedicated ML product engineers enable rapid transitions to production, often launching beta versions within weeks of successful offline testing.Our passion for machine learning drives us to explore and productize everything from conventional supervised models to advanced unsupervised clustering algorithms and innovative transformer neural network applications. We rigorously test and assess the real customer impact of every model we deploy.What Will I Be Doing?Identify opportunities where ML can generate value for our customers.Determine the optimal ML framing for product challenges.Collaborate with team members and Product and Design stakeholders.

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 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 Parallel Domain, a pioneer in creating cutting-edge simulation and digital twin platforms for advancing autonomy, robotics, and computer vision. Our Replica product specializes in generating extensive, photorealistic digital twins of real-world environments, essential for the testing, validation, and development of autonomous systems. We invite you to become part of our innovative team and contribute to shaping the future of technology.

Are you ready to redefine the potential of frontier AI models? Join Flower Labs as a founding member of the Flower Frontier Model Team, a pioneering group dedicated to creating groundbreaking models that integrate cutting-edge techniques with Flower’s innovative decentralized learning methods. This position offers a unique opportunity to explore a transformative approach that not only facilitates GPU scaling but also accesses new data silos previously untapped for frontier model training.Our mission is to develop models with superhuman capabilities across various domains, including science, health, finance, and drug discovery. This is your chance to contribute to the foundational training paradigms that will shape the next decade of AI, working on technologies that will be widely studied and emulated.About the RoleWe welcome all passionate individuals, especially those with post-training expertise, to apply.As a founding Machine Learning Engineer, you will be vital in constructing state-of-the-art large language models (LLMs) and foundation models within a compact, high-impact team of both research and engineering professionals. This role merges rapid development with disciplined software engineering, enabling you to create a reliable, maintainable, and scalable software stack that produces industry-leading open-source models and integrates them into new Flower Lab products.Your responsibilities will encompass the design, implementation, and optimization of essential components throughout all stages of frontier model development: from data curation and evaluations to pre-training and post-training. While experience in these areas is advantageous, a strong aptitude for problem-solving and collaborative learning is crucial for success. Familiarity with ML distributed and scaling strategies, as well as experience with GPU clusters for multi-node training, will be essential. You will address GPU and kernel issues, resolve memory and storage bottlenecks, and tackle multi-node failures, collaborating on debugging training instabilities and related challenges.

At SoundCloud, we empower artists and fans to connect through the power of music. Established in 2007, SoundCloud is a leading artist-first platform, enabling musicians to build and elevate their careers with cutting-edge tools, services, and resources. With a vast library of over 400 million tracks from 40 million artists, SoundCloud is shaping the future of music.We are actively seeking a Senior Machine Learning Engineer to join our Recommendations Experience team. This role focuses on developing machine learning-driven features that enhance personalization, engagement, and overall satisfaction for our users. In this position, you will leverage strong engineering principles while working across the entire technology stack, from data pipelines and APIs to real-time serving systems. The Recommendations team is responsible for deploying ML-powered features that connect over 200 million users with music tailored to their preferences.In this role, you will take ownership of features from conception to deployment: collaborating with Product and Design teams to understand user needs, architecting data pipelines that process billions of events, and building robust production ML systems that balance performance, cost, and user satisfaction. You will work with technologies such as BigQuery (handling trillions of rows), Airflow orchestration, real-time serving infrastructure (BigTable), and APIs, while engaging in continuous collaboration with Product, Design, Engineering, and Platform teams.Key Responsibilities:Develop, test, and productionize machine learning models.Make informed technical decisions factoring in cost, latency, complexity, and maintainability.Navigate distributed systems (BigQuery, BigTable, Airflow, DynamoDB) to create reliable and scalable solutions.