AI Research Engineer - Specialized in Reinforcement Learning

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.

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.

JetBrains is seeking a Senior Machine Learning Researcher to focus on Spectrum. This position centers on applying machine learning expertise to improve product features and contribute to ongoing research efforts. Role overview This role involves working with a team dedicated to advancing the capabilities of Spectrum. The Senior Machine Learning Researcher will use their knowledge to influence product direction and participate in research projects that drive innovation. Key responsibilities Apply machine learning methods to enhance Spectrum's technology. Contribute to research initiatives that inform future product development. Share insights and provide leadership within the research team. Locations This position is available in Amsterdam, Belgrade, Berlin, Limassol, Madrid, Munich, Paphos, Prague, Warsaw, and Yerevan.

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.

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.

About UsAt Prior Labs, we are pioneers in developing foundation models that effectively comprehend tabular data, which serves as the cornerstone of various fields including science and business. While foundation models have revolutionized the processing of text and images, structured data remains a largely untapped resource. Our mission is to address this $600 billion opportunity, fundamentally transforming the way organizations engage with scientific, medical, financial, and business data.Our Achievements: We proudly stand as the leading organization in the realm of structured data machine learning (ML). Our groundbreaking TabPFN v2 model has been featured in Nature, establishing a new benchmark in tabular machine learning. Following its release, we have significantly enhanced our model capabilities, achieving over 2.5 million downloads and receiving more than 5,500 stars on GitHub. We are witnessing a rapid uptick in adoption from both research and industry sectors as we build the next generation of tabular foundation models and commercialize them with enterprises across Europe and the United States.Our Team: Our team consists of a highly selective group of over 20 engineers and researchers, chosen from a pool of more than 5,000 applicants. We have backgrounds from industry giants 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 eminent AI researchers including Bernhard Schölkopf and Turing Award winner Yann LeCun. Meet our talented team here.What's Next: Supported by top-tier investors and leaders from Hugging Face, DeepMind, and Silo AI, we are on a rapid growth trajectory. This is an exceptional time to join us and help shape the future of structured data AI. Explore our manifesto for further insight.Core Areas of ImpactAs a member of our engineering team, you will contribute to the development of a novel class of AI models. Our latest innovation, TabPFN, significantly surpasses existing methods by orders of magnitude, and we are just getting started. This is a unique opportunity to:Engage in groundbreaking advancements in AI, rather than just incremental enhancements.Influence the future of how organizations globally manage their most critical data.Join us at an opportune moment: we have secured substantial funding (with announcements imminent), achieved strong initial traction (over 100,000 downloads), and are expanding swiftly.At Prior Labs, we prioritize collaboration and integration of research into practical applications. Our Research Engineers play a critical role in bridging the gap between innovative research and real-world implementation.

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.

Superhuman embraces a dynamic hybrid work model for this internship. This flexible approach allows team members to enjoy focused work time while also benefiting from in-person collaboration that fosters trust, innovation, and a strong team culture.About SuperhumanSuperhuman, which includes Grammarly as part of its AI productivity platform, is dedicated to unlocking the superhuman potential within everyone. Our suite of applications and agents integrates seamlessly with over 1 million apps and websites, enhancing productivity through innovative tools. Our offerings include Grammarly’s writing assistance, Coda’s collaborative workspaces, and Go, a proactive AI assistant that understands context and delivers automated help. Since our founding in 2009, we have empowered over 40 million individuals and 50,000 organizations globally, including 3,000 educational institutions, to eliminate busywork and focus on what truly matters. Discover more at superhuman.com.The OpportunityTo achieve our ambitious goals, we are seeking a motivated PhD student to join our Research team for a 3-month internship in the summer of 2026. Ideal candidates should be nearing the completion of their Master’s or PhD studies and possess a strong background in natural language processing (NLP), machine learning (ML), and deep learning (DL). Flexible start dates are available within the summer months.In this role, the intern will engage with a variety of complex challenges associated with modern LLMs, including writing assistance, personalization, AI detection, and more. Our Research team actively contributes to leading journals and participates in conferences while developing next-generation features and products for tens of millions of daily active users.Superhuman’s engineers and researchers are empowered to innovate and achieve breakthroughs, directly influencing our product roadmap. As our technical challenges grow with the scaling of our interfaces, algorithms, and infrastructure, you can learn more about our team's work on our technical blog.As an Applied Research Intern, you will be pivotal in addressing some of Superhuman’s most significant research challenges. Your responsibilities will include:Engaging in an end-to-end research challenge that aligns with your team’s strategic goals.Collaborating with a mentor to scope, design, and execute a well-defined project throughout your internship.Working closely with other team members to share insights and drive innovation in your area of focus.

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.

Role Overview Reprisk is hiring a Senior Machine Learning Engineer in Berlin. This position focuses on building and improving machine learning systems that support risk management products. The role centers on strengthening data processing and improving predictive models used throughout the company.

About UsHelsing is a pioneering defense AI company dedicated to safeguarding democracies. Our mission is to achieve technological leadership, ensuring that open societies can maintain sovereignty over their decisions and ethical standards.As advocates for democratic values, we recognize our profound responsibility in the thoughtful advancement and application of transformative technologies like AI. We take this commitment seriously.Our team consists of passionate engineers, AI specialists, and customer-oriented program managers. We are on the lookout for mission-driven individuals to join our European teams and leverage their skills to tackle the most complex and impactful challenges. We foster an open and transparent culture that encourages healthy discussions about the utilization of technology in defense, its advantages, and its ethical considerations.The RoleAt Helsing, we are revolutionizing perception by developing foundational intelligence for the physical world. You will engage in researching, designing, and training large-scale Foundational Models that convert intricate multimodal sensor data into innovative autonomous capabilities.We are in search of an individual who operates at the nexus of AI Research and Machine Learning Engineering, possessing a proven background in LLM/VLM (multimodal) architectures. Your core responsibility will involve training and fine-tuning Vision-Language Models using our proprietary datasets to enhance our diverse product offerings. You will oversee the entire model lifecycle, from data curation and training to evaluation.

Delivery Hero SE seeks a Principal Machine Learning Engineer to join the Vendor Data Team in Berlin. This position centers on transforming vendor data into insights that support business operations and strategy. Role overview The Principal Machine Learning Engineer will lead efforts to design and deploy machine learning models tailored to vendor data. The goal is to create tools and systems that translate complex information into practical recommendations for the company. What you will do Lead the design and development of machine learning solutions focused on vendor data. Guide the team in using advanced technologies to address real business needs. Convert complex datasets into actionable recommendations that improve operations and support decision-making. Location This role is based in Berlin.

About UsAt Prior Labs, we are pioneering the development of foundation models designed to comprehend tabular data, which serves as the cornerstone of both scientific and business endeavors. While foundation models have revolutionized the way we process text and images, the potential of structured data remains largely untapped. We are seizing a monumental $600B opportunity to redefine how organizations interact with scientific, medical, financial, and business datasets.Our Momentum: We are recognized as the global leader in structured data machine learning. Our groundbreaking TabPFN v2 model, featured in Nature, has set a new benchmark for tabular machine learning. Since its launch, we have scaled our model's capabilities by over 20 times, achieving more than 2.5 million downloads and garnering over 5,500 stars on GitHub. Our technology is rapidly gaining traction in both research and industry, paving the way for the next generation of tabular foundation models which we are actively commercializing with leading enterprises across Europe and the US.Our Team: We are a selective and dynamic group of over 20 engineers and researchers, handpicked from a pool of more than 5,000 applicants. Our diverse backgrounds include industry giants 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 eminent AI researchers, including Bernhard Schölkopf and Turing Award laureate Yann LeCun. Discover more about our team here.Join Us: With support from top-tier investors and leaders from Hugging Face, DeepMind, and Silo AI, we are experiencing rapid growth. This is your chance to help shape the future of structured data AI. Read our manifesto.Your Impact AreasAs a Research Scientist Intern, you will be at the forefront of collaborating on a novel class of AI models that go beyond mere incremental improvements. At our early-stage startup focused on foundation models for tabular data, you will encounter a myriad of thrilling research opportunities and challenges that align with your interests and expertise. Our initiatives include:Enhancing our transformer architectures to effectively handle datasets from 10K to over 1M samples without sacrificing performance.Developing multimodal models that integrate textual and tabular data on proprietary datasets.Creating tailored architectures for time series analysis, forecasting, and anomaly detection.

Axel Springer SE seeks a Staff or Senior Software Engineer specializing in Machine Learning to join the Berlin team. This role influences how the organization applies technology to reach and engage its audience. Key Responsibilities Design and improve machine learning algorithms for practical, real-world use. Collaborate with colleagues across departments to deliver meaningful projects. Contribute to the growth and enhancement of data-driven products and solutions. What We Value Creative approaches to solving complex technical challenges. Initiative and motivation to drive projects forward. Curiosity about new technologies and their practical applications. This position offers the chance to shape technology at Axel Springer SE and work on projects that reach a broad audience.

Delivery Hero is looking for a Senior Python AI Engineer to focus on logistics, data, and machine learning projects in Berlin. This position centers on developing AI-powered tools that support and improve delivery operations. Role overview This role involves designing and building applications using Python, with a strong emphasis on artificial intelligence and data science. The main goal is to create solutions that make logistics processes more efficient and help raise customer satisfaction. What you will do Develop and maintain AI-driven applications tailored for logistics challenges Apply machine learning techniques to optimize delivery workflows Work closely with teams to identify and solve data-related problems Requirements Extensive experience with Python Background in artificial intelligence, data science, and machine learning Ability to build solutions that improve operational efficiency

Role Overview Delivery Hero SE is looking for a Senior Software Engineer focused on Machine Learning to join the quick commerce group in Berlin. This role centers on building and refining machine learning solutions that support and improve our rapid delivery operations. What You Will Do Design, implement, and optimize machine learning algorithms and models for quick commerce applications. Work closely with cross-functional teams to translate business needs into technical solutions. Apply machine learning expertise to boost operational efficiency and enhance customer experience. Contribute to projects that help Delivery Hero respond quickly to changing market demands. About the Team Join a group of engineers and specialists dedicated to advancing Delivery Hero’s quick commerce services. Collaboration across teams is a core part of the work, with each member’s input shaping the direction and impact of our products.